Measurement of serum lipoproteins

ABSTRACT

Although a more accurate estimate of a person&#39;s risk of cardiovascular disease can be made on the basis of the number of lipoprotein particles per unit volume in the person&#39;s blood, current methods all rely on measuring the mass of lipoprotein cholesterol per unit volume. It has been discovered that a rapid and accurate lipoprotein particle count can be obtained by photometry. A method and apparatus are provided for measuring the number of lipoprotein particles in a sample using photometry.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/408,527, filed Dec. 16, 2014 (pending). U.S. patent application Ser.No. 14/408,527 is a U.S. national stage under 35 U.S.C. 3.71 ofInternational patent application number PCT/US2013/046170 (published).International Application number PCT/US2013/046170 cites the priority ofU.S. provisional patent application Ser. No. 61/815,503, filed Apr. 24,2013. International Application number PCT/US2013/046170 is acontinuation in part of U.S. patent application Ser. No. 13/842,577,filed Mar. 15, 2013, issued as U.S. Pat. No. 9,239,280 on Jan. 19, 2016.U.S. patent application Ser. No. 13/842,577 cites the priority of U.S.provisional patent application Ser. No. 61/660,710, filed Jun. 16, 2012.

BACKGROUND

The measurement of blood lipoproteins is critical in predicting anindividual's risk of many chronic diseases, particularly cardiovasculardisease such as coronary heart disease (CHD). CHD continues to be theleading cause of death in the United States despite phenomenal advancesmade in its diagnosis, treatment, and prevention in the last 3 decades.As per the recently released Heart and Stroke Statistics (2012 Update bythe American Heart Association; Circulation 2012; 125:e2-e220), CHDaccounts for 1 in 6 deaths in the US. In 2008 as many as 405,309 peopledied of CHD and 785,000 were expected to have a new heart attack andanother 470,000 people with recurrent attacks. These astoundingstatistics clearly tell us that prevention of heart disease stillremains a formidable task.

Heart disease is a multi-factorial disease and several risk factors suchas high blood pressure, smoking, elevated serum low density lipoprotein(LDL) cholesterol, and diabetes are attributed to an increased risk.Among these risk factors, LDL is known to be directly responsible forthe build-up of the plaque within the arterial wall which results insubsequent coronary events. This is further supported by the fact thatlowering LDL cholesterol by pharmacological means or lifestyle changessignificantly reduces coronary events. However, only 50% of coronaryevents can be accounted by elevated LDL cholesterol and many studiessuggest that coronary events can also occur even in people with normalLDL cholesterol. Therefore, in recent years there has been a surge inresearch in identifying new risk factors and biomarkers that may explainthe CHD risk that cannot not be accounted by traditional risk factors.Some examples of emerging risk factors are high sensitivity C-ReactiveProtein (hs-CRP), homocysteine, lipoproteins other than LDL cholesterol,such as low levels of high density lipoproteins (HDL) and its subclassesHDL2 and HDL3, and non-HDL cholesterol which includes intermediatedensity lipoproteins (IDL), very low density lipoproteins (VLDL,), andlipoprotein(a) [Lp(a)] in addition to LDL cholesterol. Several otherstudies also support measurement of apolipoproteins, the proteins on thesurface of lipoprotein particles. In particular, evidence to measureserum apolipoprotein B (apo B) is compelling since all atherogeniclipoproteins (Lp(a), LDL, IDL and VLDL) contain apo B and thus trulyreflects the comprehensive risk associated with all atherogeniclipoproteins. In addition, serum apolipoprotein concentration alsoreflects the total number of atherogenic particles, which areresponsible for the plaque build-up, because each of these contain oneand only one molecule of apo B.

More recent studies also suggest that LDL particle (LDLp) concentration(or number) is also an independent risk marker and is superior to therisk predicted by routinely measured LDL cholesterol (more oftencalculated using Friedewald equation in most labs). A recent studysuggests that LDL particles, not the amount of cholesterol carried bythem, play a pivotal role in the development of atherosclerosis. Itappears that endothelial retention of intact apo B containing particlesis essential for initiation of atherosclerotic process. Thus,cholesterol in LDL molecules merely acts as ‘passenger’ while particlesact as the ‘driver’. A number of published outcome studies, which usedLDL particle number measurement by nuclear magnetic resonance (NMR),suggest LDL particle number is a significant and independent predictorof cardiovascular endpoints, including CHD death and myocardialinfarction. Most of these studies also have demonstrated that the riskassociated with elevated LDL particle number is much higher than thatassociated with LDL cholesterol.

As mentioned above there is sufficient evidence that increased numbersof lipoproteins other than LDL, such as elevated levels of atherogenicLp(a), IDL, and VLDL, and low levels of anti-atherogenic HDL, are alsostrongly and independently associated with CHD. Thus, based on theobserved clinical benefits of LDL particle concentration measurementover LDL cholesterol the measurement of particle concentration (ornumber) of other lipoproteins such as Lp(a), IDL, VLDL, and HDL wouldalso result in clinical benefit and thus diagnosis and management ofheart disease.

Even though an independent association of LDL particle number (LDLp) isknown, LDLp number (as well as the particle number of otherlipoproteins) is not commonly measured because of the following reasons.First, measurement of cholesterol is relatively easy since severalsimple enzymatic methods are available. Second, LDL cholesterol can beconveniently calculated using Friedewald equation [LDL-C=TotalCholesterol—(HDL cholesterol+0.2*triglycerides)]. Third, methods tomeasure lipoprotein particle number, including LDLp, are very few, notwidely available and are complicated and expensive. The three currentlyavailable commercial assays for LDLp are based upon 1) NMR (LipoScience,NC); 2) ion mobility (Quest Diagnostics, CA); and 3) ultracentrifugationwith fluorescence detection (Spectracell, TX). Furthermore, the abovemeasurement methods do not measure the particle number of alllipoprotein classes. As a result, the particle number measurementmethods cannot meet the demand for this widely required test.

Consequently, there is a long-felt but unmet need in the art to developnewer, simpler, and more accurate methods for the measurement oflipoprotein particle number, including, but not limited to, HDL, Lp(a),LDL, IDL and VLDL particle number. Particularly, there is a need todevelop newer, simpler, and more accurate methods the measurement oflipoprotein particle number, including, but not limited to, HDL, Lp(a),LDL, IDL and VLDL particle number, which can be performed inexpensivelyin the clinical context, and which has the ability to enumerateparticles of all significant types of lipoprotein. The presentdisclosure addresses such needs.

SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding of some aspects of the claimed subject matter. Thissummary is not an extensive overview. It is not intended to identify keyor critical elements or to delineate the scope of the claimed subjectmatter. Its sole purpose is to present some concepts in a simplifiedform as a prelude to the more detailed description that is presentedlater.

The disclosure provides methods and apparatuses for determining (i.e.counting) lipoprotein particle numbers in a sample. In one aspect, thesample is a blood sample. In another aspect the sample is a blood serumsample. In one aspect, the lipoprotein particle number is determinedphotometrically. It has been unexpectedly discovered that photometricmeasurements of lipoproteins in a sample provide a rapid, inexpensive,and accurate determination (count) of lipoprotein particle number. Ithas also been unexpectedly discovered that photometric measurement canbe used effectively to determine (count) lipoprotein particle numbers insample that has been fractionated to provide for separation of thevarious classes of lipoprotein particles. The fractionation may be acomplete or partial fractionation. In one aspect, density-gradientultracentrifugation is used as the fractionation technique. In oneaspect, light scattering measurements are employed as the photometricmeasurement. The methods disclosed have been found to provide accuratedetermination (count) of lipoprotein particle number and to be robust inthe presence of blood and serum components.

A general embodiment of the method comprises obtaining a photometricmeasurement of a serum lipid fraction from a subject and calculating aparticle count for at least one serum lipid in the serum lipid fraction,where the particle count is a function of the photometric measurement.In one aspect, the photometric measurement is a measurement of lightscattering caused by the serum lipid. The serum lipid fraction may befractioned, either completely or partially, prior to the photometricmeasurement being obtained.

Another general embodiment of the method comprises obtaining aphotometric measurement of a lipoprotein particle in a serum lipidfraction from a subject and calculating a particle count for at leastone lipoprotein particle in the lipid fraction, where the particle countis a function of the photometric measurement. In one aspect, thephotometric measurement is a measurement of light scattering caused bythe lipoprotein particle. The serum lipid fraction may be fractioned,either completely or partially, prior to the photometric measurementbeing obtained.

A more particular embodiment of the method comprises separating at leastan LDL fraction in a sample, obtaining a measurement of the lightscattering from the LDL fraction and calculating a particle count forthe LDL fraction, wherein the particle count is a function of themeasurement of light scattering. The method may further compriseseparating additional fractions in the sample in addition to the LDLfraction, such as a an HDL fraction, a Lp(a) fraction, an IDL fractionand a VLDL fraction, obtaining a measurement of the light scatteringfrom at least one of the additional fractions and calculating a particlecount for each of the additional fractions from which a light scatteringmeasurement was obtained, wherein the particle count is a function ofthe measurement of light scattering.

A more particular embodiment of the method comprises separating at leastan LDL fraction and an IDL fraction in a sample, obtaining a measurementof the light scattering from at least one of the LDL and IDL fractionsand calculating a particle count for each of the fractions from which alight scattering measurement was obtained, wherein the particle count isa function of the measurement of light scattering. The method mayfurther comprise separating additional fractions in the sample inaddition to the foregoing, such as a an HDL fraction, a Lp(a) fractionand a VLDL fraction, obtaining a measurement of the light scatteringfrom at least one of the additional fractions and calculating a particlecount for each of the additional fractions from which a light scatteringmeasurement was obtained, wherein the particle count is a function ofthe measurement of light scattering.

A more particular embodiment of the method comprises separating at leastan LDL fraction, an IDL fraction and a VLDL fraction in a sample,obtaining a measurement of the light scattering from at least one of thefractions and calculating a particle count for each of the fractionsfrom which a light scattering measurement was obtained, wherein theparticle count is a function of the measurement of light scattering. Themethod may further comprise separating additional fractions in thesample in addition to the foregoing, such as a Lp(a) fraction and a HDLfraction in a sample, obtaining a measurement of the light scatteringfrom at least one of the additional fractions and calculating a particlecount for each of the additional fractions from which a light scatteringmeasurement was obtained, wherein the particle count is a function ofthe measurement of light scattering.

In one embodiment, the method comprises separating at least an HDLfraction, an LDL fraction, an IDL fraction and a VLDL fraction in asample, obtaining a measurement of the light scattering from at leastone of the fractions and calculating a particle count for each of thefractions from which a light scattering measurement was obtained,wherein the particle count is a function of the measurement of lightscattering. The method may further comprise separating an Lp(a)fraction, obtaining a measurement of the light scattering from the Lp(a)fraction and calculating a particle count for the Lp(a) fraction,wherein the particle count is a function of the measurement of lightscattering.

In one embodiment, the method comprises separating at least an HDLfraction, an Lp(a) fraction, an LDL fraction, an IDL fraction and a VLDLfraction in a sample, obtaining a measurement of the light scatteringfrom at least one of the fractions and calculating a particle count foreach of the fractions from which a light scattering measurement wasobtained, wherein the particle count is a function of the measurement oflight scattering.

In one embodiment, the method comprises separating at least an HDLfraction in a sample, obtaining a measurement of the light scatteringfrom the HDL fraction and calculating a particle count from the HDLfraction, wherein the particle count is a function of the measurement oflight scattering.

In one embodiment, the method comprises separating at least an Lp(a)fraction in a sample, obtaining a measurement of the light scatteringfrom the Lp(a) fraction and calculating a particle count from the Lp(a)fraction, wherein the particle count is a function of the measurement oflight scattering.

In one aspect of the foregoing methods, a particle count is obtained fora fraction other than the LDL fraction, such as a HDL fraction, an Lp(a)fraction, an IDL fraction and a VLDL fraction.

An apparatus for determining a lipoprotein particle count from a sampleis provided. A general embodiment of the apparatus comprises acontaining means for containing a liquid sample having stratifiedlipid/lipoprotein fractions, a conveying means for conveying the samplefrom the containing means to a means for counting particles and meansfor counting particles configured to receive the sample from thecontaining means by way of the conveying means.

Another general embodiment of the apparatus comprises a sample vesselcontaining the sample having stratified lipid/lipoprotein fractions; aliquid conduit positioned to collect the sample from the bottom of thesample vessel; and a light scattering counter positioned to receive thesample from the conduit.

Also provided is a method of calibrating the measurement of particlecount of an atherogenic lipoprotein comprising obtaining a photometricmeasurement of an atherogenic lipoprotein from a calibration sample,measuring the molar concentration of apolipoprotein B (apoB) in thecalibration sample, and calculating a regression between the photometricmeasurement and the molar concentration of apoB.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is an exemplary particle concentration profile collected with alight scattering detector showing a profile with low amounts of Lp(a)and IDL showing a distinct peak corresponding to HDL, LDL and VLDL.

FIG. 1B is an exemplary particle concentration profile collected with alight scattering detector showing a profile with a distinct Lp(a) peakand also showing distinct HDL, LDL and VLDL peaks.

FIG. 1C is an exemplary particle concentration profile collected with alight scattering detector showing a distinct IDL peak and also showingdistinct HDL, LDL and VLDL peaks.

FIG. 1D is an exemplary deconvoluted profile corresponding to theparticle concentration profile shown in FIG. 1A.

FIG. 1E is an exemplary deconvoluted profile corresponding to theparticle concentration profile shown in FIG. 1B.

FIG. 1F is an exemplary deconvoluted profile corresponding to theparticle concentration profile shown in FIG. 1C.

FIG. 2 shows an exemplary particle calibration curve for LDL.

FIG. 3 shows an exemplary particle calibration curve for Lp(a).

FIG. 4 shows an exemplary particle calibration curve for IDL.

FIG. 5 shows an exemplary particle calibration curve for VLDL.

FIG. 6 shows an exemplary particle calibration curve for HDL.

FIG. 7A shows a deconvoluted profile of a sample having a lowtriglyceride count (94 mg/dL) analyzed under the separation conditionsreferenced as Condition 2.

FIG. 7B shows a deconvoluted profile of a sample having a lowtriglyceride count (94 mg/dL) analyzed under the separation conditionsreferenced as Condition 1.

FIG. 7C shows a deconvoluted profile of a sample having a hightriglyceride count (437 mg/dL) analyzed under the separation conditionsreferenced as Condition 2.

FIG. 7D shows a deconvoluted profile of a sample having a hightriglyceride count (437 mg/dL) analyzed under the separation conditionsreferenced as Condition 1.

FIG. 8A shows a particle concentration profile collected with a lightscattering detector illustrating a profile run under separationCondition 3 for resolution of HDL.

FIG. 8B shows the deconvoluted profile corresponding to the particleconcentration profile shown in FIG. 8A.

FIG. 9A shows a particle concentration profile collected with a lightscattering detector illustrating a profile run under separationCondition 4 for resolution of Lp(a).

FIG. 9B shows the deconvoluted profile corresponding to the particleconcentration profile shown in FIG. 9A.

FIG. 10 shows a schematic illustration of one embodiment of theapparatus of the present disclosure.

FIG. 11 shows an exemplary particle concentration profile collected witha light scattering detector showing a normal lipid profile with threewell-resolved peaks for the HDL, LDL, and VLDL fractions.

FIG. 12 shows an exemplary particle concentration profile collected witha light scattering detector showing a profile with a high LDL lipidprofile with three well-resolved peaks for the HDL, LDL, and VLDLfractions.

FIG. 13 shows an exemplary particle concentration profile collected witha light scattering detector showing a profile with a high Lp(a) lipidprofile in which the Lp(a) peak falls between the HDL peak and LDL peak.

FIG. 14 shows an exemplary particle concentration profile collected witha light scattering detector showing a profile with a high IDL lipidprofile in which the IDL peak falls between the LDL peak and VLDL peak.

FIG. 15 shows the deconvoluted profile corresponding to the particleconcentration profile shown in FIG. 11.

FIG. 16 shows the deconvoluted profile corresponding to the particleconcentration profile shown in FIG. 12.

FIG. 17 shows the deconvoluted profile corresponding to the particleconcentration profile shown in FIG. 13.

FIG. 18 shows the deconvoluted profile corresponding to the particleconcentration profile shown in FIG. 14.

FIG. 19 shows a linearity graph for HDL.

FIG. 20 shows a linearity graph for Lp(a).

FIG. 21 shows a linearity graph for LDL.

FIG. 22 shows a linearity graph for IDL.

FIG. 23 shows a linearity graph for VLDL.

FIG. 24 shows a comparison of LDL particle number as determined by themethods described herein (using Condition 2 as the centrifugationcondition) to apo B concentration as determined by the Abbott/ArchitectC8000 immunoassay.

FIG. 25 shows a comparison of LDL particle number as determined by themethods described herein (using Condition 2 as the centrifugationcondition) to LDL particle number as determined by an NMR assay(LipoScience).

FIG. 26 shows a comparison of IDL particle number as determined by themethods described herein (using Condition 2 as the centrifugationcondition) as compared to cholesterol concentration in the IDL peak asdetermined by the VAP assay (Atherotech, Inc.).

FIG. 27 shows a comparison of VLDL particle number as determined by themethods described herein (using Condition 2 as the centrifugationcondition) as compared to cholesterol concentration in the VLDL peak asdetermined by the VAP assay (Atherotech, Inc.).

FIG. 28 shows a comparison of HDL particle number as determined by themethods described herein (using Condition 3 as the centrifugationcondition) to Apo AI concentration as determined by the Abbott/ArchitectC8000 immunoassay.

FIG. 29 shows a comparison of Lp(a) particle number as determined by themethods described herein (using Condition 4 as the centrifugationcondition) as compared with Lp(a) concentration as determined by theRandox Laboratories Lp(a) immunoassay.

FIG. 30 shows an exemplary set of curves generated by varying theparameters of the Weibull equation.

FIG. 31 shows an example of deconvolution of a particle concentrationprofile collected with a light scattering detector, with the continuousprofile being deconvoluted into 14 subcurves.

FIG. 32 shows an example of grouping and summing the subcurves shown inFIG. 31 into higher level curves representative of the lipoproteinclasses.

DETAILED DESCRIPTION A. Definitions

With reference to the use of the word(s) “comprise” or “comprises” or“comprising” in the foregoing description and/or in the followingclaims, unless the context requires otherwise, those words are used onthe basis and clear understanding that they are to be interpretedinclusively, rather than exclusively, and that each of those words is tobe so interpreted in construing the foregoing description and/or thefollowing claims.

The term “individual”, “subject” or “patient” as used herein refers toany animal, including mammals, such as mice, rats, other rodents,rabbits, dogs, cats, swine, cattle, sheep, horses, or primates, andhumans. The term may specify male or female or both, or exclude male orfemale.

The term “about” as used herein refers to a value that is within a rangearound a central value, the range being a margin of error that would beexpected by one of ordinary skill in the art based on accepted methodsof measurement of the particular central value.

The terms “approximate” and “approximately” as used herein refer to adifference between an actual relationship between two variables and acalculated regression between the two variables that is relativelyminor. For example, such a relationship with a variance above 0.5 orbelow −0.5 could be said to approximate the calculated regression.

B. Lipoproteins

Prior to describing the methods and apparatus disclosed herein, thenature and functions of lipoprotein particles are discussed.Lipoproteins are spherical particles circulating in the blood whoseprimary function is to provide fuel in the form of fat and cholesterol.Cholesterol is an essential structural component of cell wall and aprecursor to many hormones. Thus all lipoprotein particles consist of adense hydrophobic core tightly packed with triglycerides (the mainsource of energy) and cholesterol ester surrounded by a thin hydrophiliclayer consisting of phospholipids, free cholesterol, and unique proteinscalled apolipoproteins. This structural arrangement allows the easytransport of these particles in the hydrophilic medium of blood fromtheir origin in the gut and liver to the peripheral cells. The chemicalcomposition of lipoproteins varies depending upon their function,origin, and metabolic state, and results in different densities andsizes of lipoproteins. Thus, lipoproteins are primarily classified basedon their density into the following classes: HDL, Lp(a), LDL, IDL andVLDL. HDL is a lipoprotein rich in proteins. LDL is a lipoprotein richin cholesterol and containing decreased amounts of triglyceride (TG).VLDL lipoproteins are rich in TG. Lp(a), which is an LDL particle with aunique protein called apolipoprotein(a) attached to the apoB molecule ofthe LDL particle through a disulfide bond; Lp(a) particle share many ofthe characteristics of LDL particles. IDL lipoproteins have a densitybetween LDL and VLDL and are rich in TG but low in cholesterol.

Since all lipoproteins have similar structural components (i.e., allcontain cholesterol, triglycerides, and phospholipids) with uniqueapolipoproteins their separation for the purpose of quantitation basedon chemical composition is difficult. As a result, the differentphysical parameters of lipoproteins, such as, but not limited to,density and size, are most commonly utilized for separation purposes.Ultracentrifugation and electrophoresis are the most common and acceptedseparation methods, although methods based on chemical composition haverecently emerged.

C. General Overview of Method

The measurement of lipoprotein particle concentration (number) is basedon the direct relationship between the number of lipoprotein particlespresent in a given volume of sample and the area under the lipoproteinpeak as determined by the detector. As discussed herein, during theseparation step, (such as, but not limited to, ultracentrifugation)lipoproteins are separated based upon their respective densities. Whenultracentrifugation is used in the separation step, the HDL migrates tothe bottom of the centrifuge tube, LDL migrates to the middle of thetube, and VLDL migrates to the top of tube. Lp(a) migrates between HDLand LDL, and IDL migrates between LDL and VLDL. Thus, as lipoproteinselute sequentially from the bottom of the centrifuge tube and passthrough the detector (such as photometric detector or a light scatteringdetector as discussed in more detail herein), a signal is generated bythe detector. The signal from the detector is output as a continuouscurve corresponding to particle concentration profile, with peakscorresponding to the various lipoproteins (including HDL and otherproteins, Lp(a), LDL, IDL, and VLDL) that are present in the sample.

When a light scattering detector is used, the detector output is acontinuous curve corresponding to the scattered light intensity (involt-minutes) (described in more detail herein). Three examples ofparticle concentration profiles collected with a light scatteringdetector are shown in FIG. 1A-C. The profiles shown in FIG. 1A-C wereobtained using the centrifugation conditions described as Condition 1herein and using the apparatus and methods disclosed in more detailherein. FIG. 1A is a profile with low amounts of Lp(a) and IDL showing adistinct peak corresponding to HDL, LDL and VLDL; FIG. 1B is a profileshowing a distinct Lp(a) peak and also showing distinct HDL, LDL andVLDL peaks; and FIG. 1C is a profile showing a distinct IDL peak andalso showing distinct HDL, LDL and VLDL peaks.

As can be seen from the profiles in FIGS. 1A-C, the separation oflipoprotein peaks from each other does not reach baseline separationsince the separation procedure used, in this case ultracentrifugation,is a rapid non-equilibrium density gradient ultracentrifugation suitablefor higher throughput required by a clinical laboratory. Thus,quantitation of each lipoprotein requires a mathematical deconvolutionprocess to calculate the corresponding areas under the respectivelipoprotein peaks. The deconvolution process quantifies lipoproteinpeaks in terms of their respective peak areas, which can be used todetermine particle concentration as described herein.

The deconvolution process uses a general purpose computer to record theoutput from the detector. The deconvolution process is based upon thepeak shapes (peak widths at half-height and exponential tails) and sizes(peak height) expected and observed from the isolated individuallipoprotein classes from preparative ultracentrifugation. Fittedsubcurves are configured to align with the shapes (peak width andexponential tail) and size (peak height) of the peaks on the maincontinuous curve. Furthermore, subcurve peak positions and shapes andsizes are adjusted so as to minimize the difference between the totalarea under the main continuous response curve from the detector and sumof the areas under all subcurves. The software uses a least-squarenon-linear regression analysis to minimize the area between the mainresponse curve from the detector and sum of the subcurves correspondingto individual lipoprotein peaks.

Exemplary deconvoluted profiles corresponding to raw profiles generatedfrom the output of the detector as shown in FIGS. 1A-C are shown inFIGS. 1D-F. As can be seen, the deconvolution process generatessubcurves for the lipoprotein classes discussed herein. From suchsubcurves, the area under each subcurve is calculated as is known in theart.

The area under each subcurve is then converted to a particleconcentration (nmol/L) using a calibration procedure. Since all fivelipoprotein classes have different sizes and varying composition, theamount of light scattered from each lipoprotein type of particle isdifferent (for example, IDL is larger than LDL so an IDL particlescatters a greater amount of light than an LDL particle). Therefore,each lipoprotein class requires a separate calibration curve.

Since there are no materials available with known concentration oflipoprotein particles, a novel approach using a marker specific for agiven lipoprotein particle was used. While a number of specific markersmay exist and be used, in the present disclosure the specific marker forthe atherogenic lipoproteins (Lp(a), LDL, IDL and VLDL) was apo B andthe specific marker for HDL was apo A1. From the art, it is known thateach atherogenic lipoprotein particle contains one and only one apo Bmolecule and that each particle of HDL contains from 2-5 particles ofapo A1. Thus, the number of lipoprotein particles in a given fractioncan be calculated if the marker concentration in that fraction is known.

Fractions are collected for analysis of the marker and the amount ofmarker in the sample is determined (such as through the use of animmunoassay) in mg/dL. Since the volume of the fraction is known, theconcentration of marker in mg may be determined. The molar concentrationof marker is then determined using the molecular weight of the marker.In addition, the area under a given lipoprotein curve is directlyproportional to the number or concentration of lipoprotein particles.Thus, if the area under a lipoprotein curve is calibrated usingmaterials with known amount of a specific marker, one can calculate theamount of the marker in a lipoprotein peak of unknown patient (in moles)using calibration curve method (as commonly used for many diagnostictests) and thus the number of LDL or other lipoprotein particles (usingAvogadro's concept).

A specific example of the calibration procedure is provided using LDL asan example. Calibration procedures for the remaining atherogeniclipoproteins will be carried out in the same manner. For calibration,fresh patients serum samples with a wide ranging apo B concentration(previously determined using immunoassay methods) were used ascalibration materials. The calibration samples are subject to separationas described herein; in one embodiment, the separation and analysisprocedure for the calibration samples is the same as the separationprocedure used for determining lipoprotein particle concentration in anunknown sample (for example, Conditions 1 and/or 2 as described herein).Rather than analyzing the centrifugate using a photometric detector, thefractions are collected for measurement of the concentration of apo B,the specific marker. Any method of apo B measurement may be used. In oneaspect, an immunoassay method, such as the Abbott/Architect C8000system, is used to determine apo B amount in mg/dL. The concentration ofapo B in absolute mg in each fraction can be calculated by knowing thevolume of each fraction (which can be measured easily). On examining theprofile curves generated, for example profile curves from the samesample, one can determine which of the examined fractions correspond tothe LDL peak (or any desired lipoprotein peak). The fractionscorresponding to LDL are summed to yield a final apo B amount. The apo Bamount is used as Y axis and the LDL peak area as X-axis to plot thecalibration curve. The process is repeated for each sample to generate acalibration curve.

In order to find apo B concentration in LDL of unknown sample, equation1 is usedY=mx+c  Equation 1

-   Y is the LDL apo B concentration which is to be determined;-   m is the slope of calibration curve;-   x is the LDL peak area in V·min; and-   C is intercept of calibration curve.

An example of calibration curve for LDL is shown in FIG. 2. Exemplarycalibration curves for Lp(a), IDL and VLDL are shown in FIGS. 3-5. Thepeak area represents the volt-minutes under the peak obtained using alight scattering detector after the LDL fraction had been separated fromthe other serum components by density-gradient centrifugation. ApoB massin the LDL fraction was determined by commercial immunoassay.

Once the amount of apo B in the LDL peak of an unknown sample iscalculated from the calibration curve it can be converted to particlenumber (nmol/L) using equation 2:Z _(LDL) =A/(V×MW _(apoB))  Equation 2

-   Z_(LDL) is the LDL particle number or concentration (nmol/L)-   A=LDL apo B concentration in mg×10¹²-   V=actual serum volume used in μls-   MW_(apoB)=molecular weight of apo B (550,000 Da)

An additional specific example of the calibration procedure is providedusing HDL. The process is carried out as described above, with theexception that apo AI is used as the marker. However, unlike thepresence of a single apo B molecule on all atherogenic lipoproteins,such as LDL, IDL, VLDL, and Lp(a), the number of Apo AI molecules on HDLparticle is known to vary from 2 to 5. Although there are methodsavailable to measure the number of Apo AI molecules on HDL particle, forthe sake of simplicity it is assumed that each HDL particle contains 3molecules of Apo AI. An example of calibration curve for HDL is shown inFIG. 6. The peak area represents the volt-minutes under the peakobtained using a light scattering detector after the LDL fraction hadbeen separated from the other serum components by density-gradientcentrifugation. Apo AI mass in the HDL fraction was determined bycommercial immunoassay.

In order to find apo B concentration in LDL of unknown sample, equation1 is used as above, but the values of Y and x are as defined below.

-   Y is the HDL apo A1 concentration which is to be determined; and-   x is the HDL peak area in V·min.

Once the amount of Apo AI in the HDL peak of an unknown sample iscalculated from the calibration curve it can be converted to particlenumber (μmol/L) using equation 3:Z _(HDL) =A/(V×(3×MW _(ApoAI))  Equation 3

-   Z_(HDL) is the HDL particle number or concentration (μmol/L)-   A=HDL Apo AI concentration in mg×10¹²-   V=actual serum volume used in μls-   MW_(ApoAI)=molecular weight of apo B (28,000 Da)

D. Methods of Measuring Lipoproteins

Methods of determining lipid particle number in a sample from a subjectare provided. In one embodiment, the lipid is a lipoprotein. In anotherembodiment, the lipid is a lipoprotein selected from the groupconsisting of HDL, Lp(a), LDL, IDL and VLDL; the particle number for oneor more of the lipoproteins may be determined. In one embodiment, thesample is a blood sample. In another aspect the sample is a blood serumsample. In one embodiment, light scattering measurements are employed asthe photometric measurement.

A general embodiment of the method comprises obtaining a photometricmeasurement of a lipid fraction from a sample and calculating a particlecount for the lipid fraction, where the particle count is a function ofthe photometric measurement. The method may further comprise separatinga sample into a plurality of lipid fractions to facilitate themeasurement. In one aspect of this embodiment, the lipid is alipoprotein. In another embodiment, the lipid is a lipoprotein selectedfrom the group consisting of HDL, Lp(a), LDL, IDL and VLDL; the particlenumber for one or more of the lipoproteins may be determined. In oneaspect of this embodiment, a given lipid fraction contains only a singlelipid species or predominately a single species of lipid, such as, forexample, LDL. In one aspect, the photometric measurement is ameasurement of light scattering caused by the lipid fraction. The samplemay be fractioned, either completely or partially, prior to thephotometric measurement being obtained.

Another general embodiment of the method comprises subjecting a samplefrom a subject containing a lipid to a fractionation technique, thefractionation technique resulting in a plurality of fractions, whereinat least one of the fractions contains a lipid. Such a fractioncontaining a lipid is referred to herein as a lipid fraction. A singlesample may be fractionated into one, two, three or n^(th) lipidfractions. Not every fraction separated need contain a lipid.Furthermore, in one aspect of this embodiment, a single fractioncontains a single lipid or predominately a single lipid. In addition, inone aspect of this embodiment, a single fraction contains more than onelipid.

In one aspect of this embodiment, the method comprises separating afirst lipid fraction in a sample, obtaining a photometric measurement ofa lipid in the first lipid fraction and calculating a particle count forthe lipid in the first lipid fraction, where the particle count is afunction of the photometric measurement. Such a method may furthercomprise separating a second, third and n^(th) lipid fraction in asample, obtaining photometric measurement for at least one of thesecond, third and n^(th) lipid fractions and calculating a particlecount for at least one of the lipids contained in the second, third andn^(th) lipid fractions, wherein the particle count is a function of thephotometric measurement.

In another aspect of this embodiment, the lipid is a lipoprotein. Inanother embodiment, the lipid is a lipoprotein selected from the groupconsisting of LDL, Lp(a), LDL, IDL and VLDL; the particle number for oneor more of the lipoproteins may be determined.

Therefore, in another general embodiment, the method comprises obtaininga measurement of light scattering of a lipid fraction from a subject andcalculating a particle count for at least one lipid in the lipidfraction, where the particle count is a function of the measurement oflight scattering. In one aspect of this embodiment, the lipid is alipoprotein. In another embodiment, the lipid is a lipoprotein selectedfrom the group consisting of LDL, Lp(a), LDL, IDL and VLDL; the particlenumber for one or more of the lipoproteins may be determined. In oneaspect of this embodiment, the lipid fraction contains only a singlelipid species, such as, for example, LDL. The lipid fraction may befractioned, either completely or partially, prior to the photometricmeasurement being obtained.

Another general embodiment of the method comprises subjecting a samplefrom a subject containing a lipid to a fractionation technique, thefractionation technique resulting in a plurality of subdivisions of thesample, wherein at least one of the subdivisions contains a lipid. Sucha subdivision containing a lipid is referred to herein as a lipidfraction. A single sample may be fractionated into one, two, three orn^(th) lipid fractions. Not every fraction separated need contain alipid.

In one aspect of this embodiment, the method comprises separating afirst lipid fraction in a sample, obtaining a measurement of lightscattering of a lipid in the first lipid fraction and calculating aparticle count for the lipid in the first lipid fraction, where theparticle count is a function of the measurement of light scattering.Such a method may further comprise separating a second, third and n^(th)lipid fraction in a sample, obtaining a measurement of light scatteringfor at least one of the second, third and n^(th) lipid fractions andcalculating a particle count for at least one of the lipids contained inthe second, third and n^(th) lipid fractions, wherein the particle countis a function of the measurement of light scattering.

In another aspect of this embodiment, the lipid is a lipoprotein. Inanother embodiment, the lipid is a lipoprotein selected from the groupconsisting of LDL, Lp(a), LDL, IDL and VLDL; the particle number for oneor more of the lipoproteins may be determined.

In a further aspect of this embodiment, one or more of the plurality oflipid fractions contain a lipoprotein. In still a further aspect, two ormore, three or more, four or more or five or more of the lipid fractionscontain a lipoprotein. One or more lipid fractions may contain the samelipoprotein and the fractions be considered together when determiningthe particle number for the lipoprotein. In one aspect, the fractionscontaining the same lipoprotein are considered together using adeconvolution algorithm as described herein. As discussed above, asingle lipid fraction may contain a single lipoprotein. Furthermore, asingle lipid fraction may contain substantially a single lipoprotein.

In the following discussion, the lipid is referred to herein as alipoprotein for simplicity. The methods described herein may be used forother serum lipids as well.

In a particular embodiment of the foregoing methods, the lipoproteins inthe first, second, third and/or n^(th) lipid fractions may be separatedbased on density of the lipoprotein contained in each fraction.

In a further particular embodiment of the foregoing methods, the first,second, third and/or n^(th) lipid fractions contain only a singlespecies of lipoprotein or contain substantially only a single species oflipoprotein. The use of the term substantially as used herein withreference to a particular species of lipoproteins or other chemicalentity means that the species of lipoprotein in a given fractioncomprises 75% or more of the total lipoprotein present in the fraction(as measured on a weight to weight basis). In one embodiment, thespecies of lipoprotein in a given fraction comprises 85% or more of thetotal lipoprotein present in the fraction (as measured on a weight toweight basis). In another embodiment, the species of lipoprotein in agiven fraction comprises 90% or more of the total lipoprotein present inthe fraction (as measured on a weight to weight basis). In anotherembodiment, the species of lipoprotein in a given fraction comprises 95%or more of the total lipoprotein present in the fraction (as measured ona weight to weight basis). In another embodiment, the species oflipoprotein in a given fraction comprises 97% or more of the totallipoprotein present in the fraction (as measured on a weight to weightbasis). In another embodiment, the species of lipoprotein in a givenfraction comprises 98% or more of the total lipoprotein present in thefraction (as measured on a weight to weight basis). In anotherembodiment, the species of lipoprotein in a given fraction comprises 99%or more of the total lipoprotein present in the fraction (as measured ona weight to weight basis).

In a particular embodiment of the foregoing methods, more than one ofthe first, second, third and or n^(th) lipid fractions may each containa single lipoprotein or substantially a single lipoprotein, such as, butnot limited to, HDL, Lp(a), LDL, IDL and VLDL, and be consideredtogether in the calculations described herein. For example, the 10^(th)to 13^(th) lipid fraction may each contain LDL or substantially containLDL and be considered together in the calculations described herein fordetermining the particle number of LDL.

In a particular embodiment of the foregoing methods, the first, second,third and/or n^(th) lipid fractions may contain more than onelipoprotein in such fractions, such as, but not limited to, HDL, Lp(a),LDL, IDL and VLDL, and each fraction containing such lipoprotein orsubstantially such lipoprotein may be considered together in thecalculations described herein. For example, the 10^(th) to 13^(th) lipidfraction may each contain LDL or substantially contain LDL and beconsidered together in the calculations described herein for determiningthe particle number of LDL and the 14^(th) to 15^(th) lipid fractionsmay contain IDL or substantially contain IDL and be considered togetherin the calculations described herein for determining the particle numberof IDL.

In another, example, the 2^(cd) to 5^(th) lipid fraction may eachcontain HDL or substantially contain HDL and be considered together inthe calculations described herein for determining the particle number ofHDL, the 10^(th) to 13^(th) lipid fraction may each contain LDL orsubstantially contain LDL and be considered together in the calculationsdescribed herein for determining the particle number of LDL and the14^(th) to 15^(th) lipid fractions may contain IDL or substantiallycontain IDL and be considered together in the calculations describedherein for determining the particle number of IDL.

In yet another example, the 2^(cd) to 5^(th) lipid fraction may eachcontain HDL or substantially contain HDL and be considered together inthe calculations described herein for determining the particle number ofHDL, the 7^(th) to 9^(th) lipid fraction may each contain Lp(a) orsubstantially contain Lp(a) and be considered together in thecalculations described herein for determining the particle number ofLp(a), the 10^(th) to 13^(th) lipid fraction may each contain LDL orsubstantially contain LDL and be considered together in the calculationsdescribed herein for determining the particle number of LDL and the14^(th) to 15^(t)h lipid fractions may contain IDL or substantiallycontain IDL and be considered together in the calculations describedherein for determining the particle number of IDL

In yet another example, the 2^(cd) to 5^(th) lipid fraction may eachcontain HDL or substantially contain HDL and be considered together inthe calculations described herein for determining the particle number ofHDL, the 7^(th) to 9^(th) lipid fraction may each contain Lp(a) orsubstantially contain Lp(a) and be considered together in thecalculations described herein for determining the particle number ofLp(a), the 10^(th) to 13^(th) lipid fraction may each contain LDL orsubstantially contain LDL and be considered together in the calculationsdescribed herein for determining the particle number of LDL, the 14^(th)to 15^(th) lipid fractions may contain IDL or substantially contain IDLand be considered together in the calculations described herein fordetermining the particle number of IDL and the 17^(th) to 18^(th) lipidfractions may contain VLDL or substantially contain VLDL and beconsidered together in the calculations described herein for determiningthe particle number of VLDL.

As used herein, when the term “fraction”, “first lipid fraction”, “lipidfraction”, “lipoprotein fraction”, “HDL fraction”, “Lp(a) fraction”,“LDL fraction”, “IDL fraction”, “VLDL fraction” or similar terms is usedin the context of the methods described herein, the terms include theconcept of adding together the amounts of a given lipoprotein class inmore than one physical subdivision of the sample collected as a resultof the fractionation technique. For example, the term “separating atleast an LDL fraction in a sample” includes the concept of separating asample into one or more physical fractions by a fractionation techniqueand adding together the LDL content in one or more of such subdivisionsof the sample to determine the LDL fraction.

In a more particular embodiment of the method, the method comprisesseparating at least an LDL fraction in a sample, obtaining a measurementof the light scattering from the LDL fraction and calculating a particlecount for the LDL fraction, wherein the particle count is a function ofthe measurement of light scattering. The method may further compriseseparating at least one additional fraction in addition to an LDLfraction. Such additional fraction may include at least one of an HDLfraction, an Lp(a) fraction, an IDL fraction and a VLDL fraction. In oneaspect, the additional fraction is an IDL fraction. In another aspectthe additional fractions are an Lp(a) fraction and IDL fraction. Inanother aspect the additional fractions are an Lp(a) fraction, an IDLfraction and a VLDL fraction. In another aspect, the additionalfractions are an HDL fraction, an Lp(a) fraction and an IDL fraction. Inanother aspect, the additional fractions are an HDL fraction, an IDLfraction and a VLDL fraction. In another aspect, the additionalfractions are an HDL fraction, an Lp(a) fraction, an IDL fraction and aVLDL fraction. In another aspect, a particle count from only the LDLfraction is calculated.

In another more particular embodiment of the method, the methodcomprises separating at least an HDL fraction in a sample, obtaining ameasurement of the light scattering from the HDL fraction andcalculating a particle count for the HDL fraction, wherein the particlecount is a function of the measurement of light scattering. The methodmay further comprise separating at least one additional fraction inaddition to an HDL fraction. Such additional fraction may include atleast one of an Lp(a) fraction, a LDL fraction, an IDL fraction and aVLDL fraction. In one aspect, the additional fraction is an LDLfraction. In another aspect the additional fractions are an Lp(a)fraction and LDL fraction. In another aspect the additional fractionsare an Lp(a) fraction, an LDL fraction and an IDL fraction. In anotheraspect, the additional fractions are an Lp(a) fraction, a LDL fraction,an IDL fraction and a VLDL fraction. In another aspect, a particle countfrom only the HDL fraction is calculated.

In another more particular embodiment of the method, the methodcomprises separating at least an Lp(a) fraction in a sample, obtaining ameasurement of the light scattering from the Lp(a) fraction andcalculating a particle count for the Lp(a) fraction, wherein theparticle count is a function of the measurement of light scattering. Themethod may further comprise separating at least one additional fractionin addition to an Lp(a) fraction. Such additional fraction may includeat least one of an HDL fraction, a LDL fraction, an IDL fraction and aVLDL fraction. In one aspect, the additional fraction is an LDLfraction. In another aspect the additional fractions are a HDL fractionand a LDL fraction. In another aspect the additional fractions are a HDLfraction, an LDL fraction and an IDL fraction. In another aspect, theadditional fractions are a HDL fraction, a LDL fraction, an IDL fractionand a VLDL fraction. In another aspect, a particle count from only theLp(a) fraction is calculated.

In a further more particular embodiment of the method, the methodcomprises separating at least an LDL fraction and an IDL fraction in asample, obtaining a measurement of the light scattering from at leastone of the LDL or IDL fractions and calculating a particle count foreach of the fractions from which a light scattering measurement wasobtained, wherein the particle count is a function of the measurement oflight scattering. In one aspect of this embodiment, a light scatteringmeasurement and a particle count are obtained for both the LDL and IDLfractions. In another aspect of this embodiment, a light scatteringmeasurement and a particle count are obtained for only the LDL fractionor the IDL fraction. In another aspect of this embodiment, a lightscattering measurement and a particle count are obtained for only theLDL fraction.

In a further more particular embodiment of the method, the methodcomprises separating at least a Lp(a) fraction, an LDL fraction and anIDL fraction in a sample, obtaining a measurement of the lightscattering from at least one of the Lp(a), LDL and IDL fractions andcalculating a particle count for each of the fractions from which alight scattering measurement was obtained, wherein the particle count isa function of the measurement of light scattering. In one aspect of thisembodiment, a light scattering measurement and a particle count areobtained for each of the Lp(a), LDL and IDL fractions. In one aspect ofthis embodiment, a light scattering measurement and a particle count areobtained for each of the LDL and IDL fractions. In one aspect of thisembodiment, a light scattering measurement and a particle count areobtained for each of the Lp(a) and LDL fractions. In another aspect ofthis embodiment, a light scattering measurement and a particle count areobtained for only the LDL fraction and the IDL fraction. In anotheraspect of this embodiment, a light scattering measurement and a particlecount are obtained for only the LDL fraction.

In a further more particular embodiment of the method, the methodcomprises separating at least an LDL fraction, an IDL and a VLDLfraction in a sample, obtaining a measurement of the light scatteringfrom at least one of the LDL, IDL and VLDL fractions and calculating aparticle count for each of the fractions from which a light scatteringmeasurement was obtained, wherein the particle count is a function ofthe measurement of light scattering. In one aspect of this embodiment, alight scattering measurement and a particle count are obtained for eachof the LDL, IDL and VLDL fractions. In one aspect of this embodiment, alight scattering measurement and a particle count are obtained for eachof the LDL and IDL fractions. In another aspect of this embodiment, alight scattering measurement and a particle count are obtained for onlythe LDL fraction and the IDL fraction. In another aspect of thisembodiment, a light scattering measurement and a particle count areobtained for only the LDL fraction.

In a further more particular embodiment of the method, the methodcomprises separating at least an HDL fraction, an LDL fraction, an IDLand a VLDL fraction in a sample, obtaining a measurement of the lightscattering from at least one of the HDL, LDL, IDL and VLDL fractions andcalculating a particle count for each of the fractions from which alight scattering measurement was obtained, wherein the particle count isa function of the measurement of light scattering. In one aspect of thisembodiment, a light scattering measurement and a particle count areobtained for each of the HDL, LDL, IDL and VLDL fractions. In one aspectof this embodiment, a light scattering measurement and a particle countare obtained for each of the LDL, IDL and VLDL fractions. In one aspectof this embodiment, a light scattering measurement and a particle countare obtained for each of the LDL and IDL fractions. In another aspect ofthis embodiment, a light scattering measurement and a particle count areobtained for only the HDL fraction, LDL fraction, the IDL fraction orthe VLDL fraction. In another aspect of this embodiment, a lightscattering measurement and a particle count are obtained for only theLDL fraction.

In a further more particular embodiment of the method, the methodcomprises separating at least an HDL fraction, an Lp(a) fraction, an LDLfraction, an IDL and a VLDL fraction in a sample, obtaining ameasurement of the light scattering from at least one of the HDL, Lp(a),LDL, IDL and VLDL fractions and calculating a particle count for each ofthe fractions from which a light scattering measurement was obtained,wherein the particle count is a function of the measurement of lightscattering. In one aspect of this embodiment, a light scatteringmeasurement and a particle count are obtained for each of the HDL,Lp(a), LDL, IDL and VLDL fractions. In one aspect of this embodiment, alight scattering measurement and a particle count are obtained for eachof the LDL, IDL and VLDL fractions. In one aspect of this embodiment, alight scattering measurement and a particle count are obtained for eachof the LDL and IDL fractions. In another aspect of this embodiment, alight scattering measurement and a particle count are obtained for onlythe HDL fraction, LDL fraction, the IDL fraction or the VLDL fraction.In another aspect of this embodiment, a light scattering measurement anda particle count are obtained for only the LDL fraction.

In one aspect of the foregoing methods, a particle count is obtained foronly the LDL fraction. In one aspect of the foregoing methods, aparticle count is obtained for the LDL fraction and at least oneadditional fraction. Such additional fraction may be a HDL fraction, anLp(a) fraction, an IDL fraction, a VLDL fraction or any combination ofthe foregoing. In one aspect of the foregoing methods, the additionalfraction is an HDL fraction. In one aspect of the foregoing methods, theadditional fraction is an Lp(a) fraction. In one aspect of the foregoingmethods, the additional fraction is an IDL fraction. In one aspect ofthe foregoing methods, the additional fraction is a VLDL fraction. Inone aspect of the foregoing methods, the additional fraction is an IDLfraction and an Lp(a) fraction. In one aspect of the foregoing methods,the additional fraction is a HDL fraction, an IDL fraction and an Lp(a)fraction. In one aspect of the foregoing methods, the additionalfraction is a HDL fraction, an IDL fraction, an Lp(a) fraction and aVLDL fraction. In one aspect of the foregoing methods, the additionalfraction is an IDL fraction, an Lp(a) fraction and a VLDL fraction.

In one aspect of the foregoing methods, a particle count is obtained foronly the HDL fraction. In one aspect of the foregoing methods, aparticle count is obtained for the HDL fraction and at least oneadditional fraction. Such additional fraction may be an Lp(a) fraction,an LDL fraction, an IDL fraction, a VLDL fraction or any combination ofthe foregoing. In one aspect of the foregoing methods, the additionalfraction is an LDL fraction. In one aspect of the foregoing methods, theadditional fraction is an Lp(a) fraction. In one aspect of the foregoingmethods, the additional fraction is an IDL fraction. In one aspect ofthe foregoing methods, the additional fraction is a VLDL fraction. Inone aspect of the foregoing methods, the additional fraction is an LDLfraction. In one aspect of the foregoing methods, the additionalfraction is an Lp(a) fraction. In one aspect of the foregoing methods,the additional fraction is an Lp(a) fraction and an LDL fraction. In oneaspect of the foregoing methods, the additional fraction is an Lp(a)fraction, an LDL fraction and an IDL fraction. In one aspect of theforegoing methods, the additional fraction is an Lp(a) fraction, an LDLfraction, an IDL fraction and a VLDL fraction.

In one aspect of the foregoing methods, a particle count is obtained foronly the Lp(a) fraction. In one aspect of the foregoing methods, aparticle count is obtained for the Lp(a) fraction and at least oneadditional fraction. Such additional fraction may be a HDL fraction, anLDL fraction, an IDL fraction, a VLDL fraction or any combination of theforegoing. In one aspect of the foregoing methods, the additionalfraction is a HDL fraction. In one aspect of the foregoing methods, theadditional fraction is an LDL fraction. In one aspect of the foregoingmethods, the additional fraction is an IDL fraction. In one aspect ofthe foregoing methods, the additional fraction is a VLDL fraction. Inone aspect of the foregoing methods, the additional fraction is an Lp(a)fraction and an LDL fraction. In one aspect of the foregoing methods,the additional fraction is an Lp(a) fraction, an LDL fraction and an IDLfraction. In one aspect of the foregoing methods, the additionalfraction is an Lp(a) fraction an LDL fraction, an IDL fraction and aVLDL fraction.

In another embodiment of the method, only atherogenic lipoproteins arecounted. Such an embodiment will comprise obtaining a measurement oflight scattering from at least one atherogenic lipoprotein fraction andcalculating a particle count for each of the atherogenic lipoproteinfractions from which a light scattering measurement was obtained,wherein the particle count is a function of the measurement of lightscattering. The atherogenic lipoprotein in such fractions may beselected from the group consisting of: Lp(a), LDL, IDL, and VLDL. In aspecific embodiment the atherogenic lipoprotein is LDL. In anotherspecific embodiment the atherogenic lipoprotein is Lp(a). Lp(a) is knownto being strongly predictive of cardiovascular disease, yet there arevery few methods by which Lp(a) can be easily and accurately measured inserum samples.

The following is relevant to the methods described herein.

The subject may be any animal having lipoproteins to be measured. In theclinical setting the subject will often be a human patient, although itis conceivable that the subject will be a non-human animal in theveterinary setting. The subject may be human or non-human animal in theresearch setting. The animal in the research setting may be, forexample, any commonly used model organism.

The lipid fraction from the subject will comprise a number oflipoproteins, such as an HDL, an Lp(a), an LDL, an IDL, and/or a VLDL.The various lipoproteins may be separated into at least one lipoproteinfractions as described herein. The lipoprotein fraction may besubstantially pure such that it will be sufficiently free from othercomponents that could affect the photometric measurement that aquantitative value for the lipoprotein in the lipid fraction can beobtained. Non-interfering components that do not affect the photometricmeasurement may be present. The fraction will not be completely free ofinterfering components in every embodiment. For example, there may besome amount of another lipoprotein fraction present. In a specificexample, when lipoprotein fractions are fractionated on the basis ofdensity, there may be overlap between adjacent lipoprotein fractions.For example, there may be Lp(a) present in the HDL fraction or there maybe IDL present in the LDL fraction.

In some embodiments of the method, the lipid fraction consistsessentially of serum components. In such embodiments the fractioncontains no additional reagents, dyes, or other substances that may beadded to facilitate measurement. This is possible in such embodimentsbecause, unlike many other methods of quantifying serum lipids,including but not limited to lipoproteins, many embodiments of thephotometric methods disclosed herein do not require the addition ofreagents, dyes, fluorochromes, or the like. Any such artificiallyintroduced substances that facilitate measurements are referred toherein as “analytical reagents.” In some embodiments of the method theserum lipid fractions generated contains no substantial amount ofanalytical reagents, such that any analytical reagents present arepresent in sufficiently low concentrations that they do not affect themeasurements. In other embodiments the lipoprotein fraction contains noanalytical reagent.

E. Photometric Measurements

In the methods described herein, the particle count is calculated as afunction of a photometric measurement. In some embodiment, thephotometric measurement is light scattering. In some embodiments thefunction is approximately linear. In some embodiments the photometricmeasurement will be in the form of a curve, typically representing therelationship between run time and the readout of the detector.Characteristics of such curves generated from the photometricmeasurement include peak height and peak area; such characteristics maybe used to calculate a particle number. Peak area is calculated in avariety of ways, most often simply by multiplying the peak height byhalf of the distance from trough to trough (as if the peak were atriangle). In certain embodiment, software is provided with measuringdevices that automatically computes peak area. In cases in which twopeaks are not completely resolved, “deconvolution” transformations maybe performed to determine a poorly resolved peak area. Such methodsinvolve taking the area of an aggregate peak and subtracting thecontribution of one peak (generally the better resolved peak) todetermine the area of the remaining peak.

Deconvolution is commonly used to resolve small peaks from largeradjacent peaks. In such cases often the smaller peak is only visible asa trough between two larger adjacent peaks, wherein the trough is not asdeep as expected. The process comprises extrapolating the expected areaunder the trough between the larger peaks, subtracting the expected areaof the trough from the actual area of the actual trough, wherein thedifference in areas is the area under the smaller peak.

Examples of small lipoprotein peaks calculated by deconvolution areshown in FIGS. 8-11. The heavy black line shows actual light scatteringvalues. The thinner lines show extrapolated peaks for each of thefractions (from left to right: HDL, Lp(a), LDL, IDL, and VLDL). Theshaded peak is the IDL peak, calculated by deconvolution of the LDL andVLDL peaks. The peak marked with horizontal hash lines is the Lp(a)peak, calculated by deconvolution of the HDL and LDL peaks.

Light scattering has been discovered to effectively enumeratelipoprotein particles after separation of lipoprotein fractions andwithout the use of additional reagents or dyes. In a specific embodimentthe photometric measurement is light scattering. Light scattering may bemeasured over any detection arc, for example 360°, 180°, 90°, or 45°. Ina specific embodiment light scattering is measured over a 90° detectionarc.

F. Light Scattering Measurements

Light scattering can be measured by various means known in the art. In aparticular embodiment, light scattering is measured using a laser lightscattering detector. The detector may be a fixed-angle detector or amulti-angle detector. For a lipoprotein particle of a given type, theamount of light scattering is approximately proportional to the numberof particles per unit volume. Typically scattering is measured over aset arc, for example 360°, 180°, 90°, or 45°. In a specific embodimentlight scattering is measured over a 90° detection arc. The particlecount is an approximately linear function of light scattering, althoughthe functions may differ depending on which lipoprotein fraction isbeing measured. The function can be determined by the calibrationmethods described below.

It is foreseeable that in some instances a linear relationship betweenparticle count and light scattering for a given fraction will be linearonly over a certain range of concentrations, and that above and belowthat certain range the relationship will not be linear. In such cases,when there is an indication that the particle count is outside of therange in which the relationship is linear, the sample may be eitherconcentrated or diluted to obtain a sample with a particle count in thelinear range. The calculation of the particle count will then becorrected for the dilution or concentration of the sample.

Some embodiments of the method comprise measuring the light scatteringof more than one lipoprotein fraction, such that the light scattering ofthe highest density fraction to be measured is measured before theothers. In some such embodiments the light scattering of each fractionis measured in order of descending density. That is to say that thelight scattering of the fractions would be measured in the followingorder, with the understanding that not all of the listed fractions needbe measured: HDL, Lp(a), LDL, IDL and VLDL. As an illustrative example,if only LDL and VLDL are to be measured, LDL would be measured first,followed by VLDL. In a particular embodiment, the sample is prepared bydensity-gradient ultracentrifugation, and the sample is drained from thebottom of a tube used for such centrifugation such that the highestdensity fractions are collected first and sent to a light scatteringcounter.

Another embodiment of the method comprises measuring the particle countof a lipoprotein fraction of a sample in any of the apparatusesdisclosed below.

G. Separation of Lipids

In a particular embodiment, vertical spin density gradientultracentrifugation is used to separate lipid fractions in a sample. Inone aspect, the lipid is a lipoprotein. However, any separation meansknown in the art may be used.

Using density gradient ultracentrifugation, the lipoprotein particlesare separated in the following order (from the bottom of the densitygradient to the top of the density gradient): HDL, Lp(a), LDL, IDL andVLDL. A variety of density gradient ultracentrifugation conditions maybe used. The composition of the density gradient may impact theseparation between various lipoprotein species. The following areillustrated by way of example only and should not be interpreted aslimiting the scope of the separation techniques to density gradientultracentrifugation or as limiting the conditions employed in densitygradient ultracentrifugation to those conditions specified.

As discussed above, in some cases certain a given fraction may containmore than one type of serum lipoprotein. This phenomenon may be causedby several factors, including factors related to the concentration ofthe various lipoprotein particles in a sample, the separation technique,such as, but not limited to, density gradient ultracentrifugation, andthe equipment used in the separation itself. As discussed herein,techniques can be used to correct for this overlap, when encountered. Inaddition, specific density gradient ultracentrifugation conditions maybe employed to provide maximum resolution of the various lipoproteinclasses (such as for example, LDL, IDL and VLDL or HDL and Lp(a)) or maybe employed to provide maximum resolution of a single lipoprotein (suchas HDL, Lp(a) and/or LDL).

In one embodiment, the density gradient ultracentrifugation conditionsand parameters are varied to provide maximum resolution of each of thevarious lipoprotein classes. In another embodiment, the density gradientultracentrifugation conditions and parameters are varied to providemaximum resolution of one or more specific lipoprotein classes. In stillanother embodiment, the density gradient ultracentrifugation conditionsand parameters are varied to provide maximum resolution of HDL. In stillanother embodiment, the density gradient ultracentrifugation conditionsand parameters are varied to provide maximum resolution of Lp(a). Instill another embodiment, the density gradient ultracentrifugationconditions and parameters are varied to provide maximum resolution ofLDL.

Conditions and parameters that may be varied include, but are notlimited to, density of the layers comprising the density gradient,volume of the layers comprising the density gradient, centrifugationtime settings, acceleration setting (impacting the time it takes for thecentrifuge to reach a set RPM), deceleration settings (impacting thetime it takes for the centrifuge to come to a stop from the set RPM atthe end a specified time setting), speed of the centrifuge (measured inRPM) and temperature of the centrifugation run. The various parametersdiscussed above may be varied singly or in any combination desired.

In one embodiment, the density gradient comprises two layers of gradientmaterial (referred to as a top and bottom layer). A commonly useddensity gradient material is KBr. Other commonly used density gradientmaterials include cesium chloride, sucrose, and colloidal silicaparticles coated with polyvinylpyrrolidone (such as the product sold asPercoll®). Any density gradient solution known in the art to create therequired density range may be used. Centrifugation will be performed inan appropriate vessel, such as a centrifuge tube. A variety of suitablecentrifuge tubes are commercially available, for example fromBeckman-Coulter, of Brea, Calif. In a specific embodiment separation isachieved using a single spin.

In one aspect of this embodiment, the density of the bottom layer rangesfrom 1.10 to 1.40 g/ml, from 1.15 to 1.30 g/ml or from 1.15 to 1.25 g/mland the density of the top layer ranges from 0.5 to 1.2 g/ml, from 1.0to 1.15 g/ml or from 1.0 to 1.10 g/ml. In another aspect of thisembodiment, the density of the bottom layer is 1.21 g/ml or 1.30 g/mland the density of the top layer is 1.05 g/ml. Further, in one aspect ofthis embodiment, the volume of the bottom layer ranges from 0.2 to 4.0ml, from 0.8 to 2.5 ml or from 1 to 2 ml and the volume of the top layerranges from 1 to 4.8 ml, from 1.2 ml to 3.0 ml or from 3.0 to 4.0 ml. Inanother aspect of this embodiment, the volume of the bottom layer is 2.0ml or 1.0 ml and the volume of the top layer is 2.90 ml or 3.9 ml.

Further, in one aspect of this embodiment, the settings for theultracentrifuge are varied as follow: (i) centrifugation time from 10 to70 minutes (note that centrifugation time does not include the timerequired for deceleration of the centrifuge rotor), from 15 to 50minutes or from 20 to 40 minutes; (ii) centrifugation speed from 50,000RPM to 75,000 RPM or 60,000 to 70,000 RPM; and (iii) centrifugationtemperature from 15 to 30 degrees Celsius or from 20 to 25 degreesCelsius. Furthermore, in one aspect of this embodiment, the accelerationand deceleration settings are selected provide appropriate accelerationand deceleration profiles in order to maximize the desired separation.In one aspect, the acceleration and/or deceleration phases of the spinare set to be slow in order to minimize vibrations that may occur duringa quick acceleration and/or deceleration. In one aspect, theacceleration and/or deceleration phases of the spin are set to be fastin order to resolve a given class of lipoprotein; faster accelerationand/or deceleration settings may be used when the density/volume of oneor more layers of the density gradient, particularly the bottom layer,is increased 1.25 g/ml or 1.0 ml, respectively. For example, using aBeckman Coulter ultracentrifuge (Optima TM XL-100 K Ultracentrifuge),the acceleration and/or deceleration settings may range from 5 to 9 or 8to 9 (with 9 being the slowest setting). In another aspect of thisembodiment, the acceleration and/or deceleration settings may range from1 to 5 or 2 to 4 (with 1 being the fastest setting.

In one embodiment applicable for general separation of lipoproteins froma sample, the following conditions are used.

Condition 1 Bottom Layer KBr Density 1.21 g/mL Top Layer KBr Density1.004 g/mL Bottom Layer Volume 1.426 mL Top Layer Volume 3.56 mLCentrifugation Time Setting 36 minutes Acceleration Settings 6Deceleration Settings 6 Centrifugation Speed 65000 rpm CentrifugationTemperature 23° C.In one aspect of this embodiment, the foregoing settings are used whenthe sample has a triglyceride concentration of less than 150 mg/dL.

As discussed herein, under certain conditions more than one type oflipoprotein may be present in a particular fraction. As a result,specific ultracentrifugation conditions may be used to maximizeseparation of a specific lipoprotein from one or more otherlipoproteins.

In a particular embodiment, the density gradient ultracentrifugationconditions are used to provide maximum resolution of LDL and IDLlipoproteins. In addition, the methods for determining particle countemploy obtaining a photometric measurement of a lipoprotein anddetermining a particle count based on the photometric measurement. Whenlight scattering is used as the photometric measurements, certainlipoprotein particle may provide a greater readout (or signal) whencompared to another lipoprotein particle. As a result, the readout forequal numbers of lipoprotein particles may be greater for onelipoprotein particle than for another. The applicants have discoveredthat under certain conditions, IDL lipoprotein may be present in one ormore fractions where LDL lipoprotein is present. In addition, IDLlipoprotein particle have several-fold greater light scatteringproperties than LDL lipoprotein particles. As a result, any IDLlipoprotein particles in a LDL fraction may lead to overestimation ofthe LDL particle number. Such mixing of IDL and LDL lipoproteinparticles may occur when the IDL lipoprotein particle concentration in asample is elevated. The applicants have further found that IDLlipoprotein particle concentrations are generally elevated whentriglyceride concentrations are over 150 mg/dL. Therefore, alternateconditions for separation may be required when IDL particleconcentrations are elevated (such as, but not limited to, whentriglyceride concentrations are over 150 mg/dL). In one embodiment, thefollowing centrifugations conditions are used when triglycerideconcentrations are over 150 mg/dL.

Condition 2 Bottom Layer KBr Density 1.21 g/mL Top Layer KBr Density1.05 g/mL Bottom Layer Volume 1.0 mL Top Layer Volume 3.94 mLCentrifugation Time Setting 20 minutes Acceleration Settings 9Deceleration Settings 9 Centrifugation Speed 65000 rpm CentrifugationTemperature 23° C.

To illustrate the use of two specific centrifugation conditionsdiscussed above, the two conditions were compared for situations wherethe triglyceride concentration was less than 150 mg/dL and greater than150 mg/dL (see FIG. 7A-D). In FIG. 7, panels 7A and 7B represent thesituation where triglyceride levels are less than 150 mg/dL(specifically 94 mg/dL) and panels 7C and 7D represent the situationwhere triglyceride levels are greater than 150 mg/dL (specifically 437mg/dL). Furthermore, panels 7B and 7D represent the use of thecentrifugation conditions referenced as Condition 1 above and panels 7Aand 7C represent the use of the centrifugation conditions referenced asCondition 2 above (optimized for samples with triglyceride levels over150 mg/dL). Examination of FIG. 7-A-D shows that the use of thecentrifugation conditions referenced as Condition 2 above maintains theseparation of lipoprotein particle fractions as compared to the use ofCondition 1 above and provides accurate particle counts of the variouslipoprotein classes (compare panels 7A and 7B). The use of thecentrifugations conditions referenced as Condition 2 (7A) above provideda LDL particle count of 1238 while the use of the centrifugationsconditions referenced as Condition 1 (7B) above provided a LDL particlecount of 1248. Furthermore, it is evident that the use of thecentrifugation conditions referenced as Condition 2 above providessuperior separation of the LDL and IDL lipoprotein particle fractions inthe high triglyceride condition (compare panels 7C and 7D). The use ofthe centrifugations conditions referenced as Condition 2 (7C) aboveprovided a LDL particle count of 1955 while the use of thecentrifugations conditions referenced as Condition 1 (7D) above provideda LDL particle count of 3100, indicating that the centrifugationconditions referenced as Condition 1 above resulted in less than optimalseparation of LDL and IDL lipoprotein particles when IDL lipoproteinparticle concentration was high (such as when triglycerideconcentrations are greater than 150 mg/dL).

In a particular embodiment, the density gradient ultracentrifugationconditions are used to provide maximum resolution of HDL lipoproteins.In one embodiment, the following centrifugations conditions are used toprovide maximal separation of HDL lipoproteins.

Condition 3 Bottom Layer KBr Density 1.30 g/mL Top Layer KBr Density1.05 g/mL Bottom Layer Volume 2.0 mL Top Layer Volume 2.90 mLCentrifugation Time Setting 35 minutes Acceleration Settings 2Deceleration Settings 2 Centrifugation Speed 65000 rpm CentrifugationTemperature 23° C.

The results of using the centrifugation conditions described asCondition 3 are shown in FIGS. 8A and 8B. FIG. 8A shows theconcentration profile collected with a light scattering detector andFIG. 8B shows the corresponding deconvoluted profile. As can be seen inFIG. 8B, the HDL peak is well resolved. Furthermore, when compared tothe profile shown in FIG. 7B (using Condition 1 described above), theHDL peak is shifted to the right and an additional peak consisting ofalbumin and other proteins is resolved from the HDL peak. The Lp(a),LDL, IDL and VLDL peaks are all compressed into a single peak to the farright of the profile.

In another particular embodiment, the density gradientultracentrifugation conditions are used to provide maximum resolution ofLp(a) lipoproteins. In one embodiment, the following centrifugationsconditions are used to provide maximal separation of Lp(a) lipoproteins.

Condition 4 Bottom Layer KBr Density 1.21 g/mL Top Layer KBr Density1.05 g/mL Bottom Layer Volume 1.0 mL Top Layer Volume 3.94 mLCentrifugation Time Setting 40 minutes Acceleration Settings 9Deceleration Settings 9 Centrifugation Speed 65000 rpm CentrifugationTemperature 23° C.

The results of using the centrifugation conditions described asCondition 4 are shown in FIGS. 9A and 9B. FIG. 9A shows theconcentration profile collected with a light scattering detector andFIG. 9B shows the corresponding deconvoluted profile. As can be seen inFIG. 9B, the Lp(a) peak is well resolved. Furthermore, when compared tothe profile shown in FIG. 7B (using Condition 1 described above), theLp(a) peak is shifted to the left providing separation from otherlipoprotein particles.

H. Apparatus for Quantifying Lipoproteins

An apparatus is provided for quantifying lipoprotein particles in aplurality of serum lipid fractions. The apparatus generally functions bycollecting lipoprotein fractions from a sample one fraction at a timeand transporting each fraction to a light scattering counter. Thecounter then measures the scattered light, which can be used tocalculate the particle count for the fraction.

A general embodiment of the apparatus comprises: a liquid conduitpositioned to collect a sample from a sample vessel; and a lightscattering counter positioned to receive the sample from the conduit. Inone embodiment, the sample is collected from the bottom of the samplevessel.

The sample vessel may be any sample container known in the art. In someembodiments of the apparatus the sample vessel is a centrifuge tube. Theuse of a centrifuge tube has the advantage of using the same vessel forseparation and for sampling. The centrifuge tube may have a bottomsurface that is easily pierced by a sampler. In such embodiments aseptum may be present on the bottom surface or the bottom surface may bea relatively thin structure.

The liquid conduit may be any structure suitable for conveying theliquid in the sample to the light scattering counter. Examples of suchstructures include pipes, tubes, channels, hoses, or any other conduitsuitable for carrying liquid as known in the art. In a specificembodiment, the conduit is 8 mm (internal diameter) Teflon tubing. Inone embodiment, the liquid conduit will be positioned to collect thesample from the bottom of the vessel. This allows the collection ofvertically stratified layers, as will occur when lipoprotein fractionsare separated by density-gradient centrifugation. Some embodiments ofthe liquid conduit comprise a sampler connected to the conduit tofacilitate collection of the sample. In a specific embodiment the liquidconduit is connected to a sampling needle. The sampling needle may bepositioned to penetrate the sample vessel to as to allow the liquid fromthe sample vessel to flow through the needle into the conduit. Thediameter of the tubing may be varied to obtain a suitable flow rate ofsample; the length of the tubing and the relative elevation of thesample vessel and the counter will also affect the flow rate, as isunderstood by those skilled in the art. All of these factors may bevaried as needed.

The light scattering counter may be any suitable instrument, for examplea laser light scattering counter. It may be configured to measurescattered light across any arc, as described above. The counter maycomprise a flow cell, in which case the conduit may be connected to theflow cell so as to allow the liquid from the sample vessel to enter theflow cell wherein its light scattering properties will be measured.

The apparatus may further comprise a pump configured to pump the samplethrough the conduit to the counter. Various types of pumps may be used.In a specific embodiment the pump is a piston pump, which allows goodcontrol over the flow rate of the liquid.

The apparatus may comprise a sensor proximate to the conduit, whereinthe sensor measures a fluid property within the conduit, and whereinsaid fluid property significantly differs in air and in liquid. Thesensor is thus capable of distinguishing air from liquid in the conduit.Properties that can be used to distinguish air from liquid are wellknown in the art, and include thermal conductivity, electricalresistance, optical absorbance, and optical diffraction. Sensors capableof measuring these properties are well known in the art.

If air is detected in the conduit it might indicate that an entiresample has been taken, and that the sample vessel is now empty. In oneembodiment, the sensor transmits a signal to indicate the presence ofair in the conduit. In one embodiment, the sensor may send a signal tothe pump to cease drawing fluid from the sample vessel when air isdetected in the conduit. In some embodiments of the apparatus the sensoris connected to transmit a signal to a valve positioned on the conduit.In such embodiments the sensor may send a signal to close the valve whenair is detected in the conduit.

The apparatus may further comprise a data logger connected to thecounter. The data logger may record the data either digitally orgraphically (i.e., on a paper printout). In embodiments in which thedata are recorded on computer-readable media, the data may be furtherprocessed by a computing device. In some such embodiments the particlecount for the lipoprotein fractions is computed by the computing devicewithout direct human intervention. The resulting particle count may thenbe displayed or recorded. The term “computer-readable media” as usedherein refers to a medium of storing information that is configured tobe read by a machine. Such media include magnetic media, optical media,and paper media (punch cards, paper tape, etc.). Printed writing in ahuman language, if not intended or configured to be read by a machine,is not considered a computer-readable medium. In no case shall a humanmind be construed as “computer-readable format.”

The apparatus may also comprise a filter positioned on the conduitbetween the sample vessel and the counter. The filter functions toremove additional interfering particles. The pore size of the filtermust be greater than the diameter of the lipoprotein to be counted.Ideally the pore size of the filter will be only slightly greater thanthe diameter of the lipoprotein to be counted, although it is to beunderstood that most classes of lipoprotein show a range of sizes.Filters with 100 nm pore size are quite suitable; they are readilyavailable commercially and remove a significant amount of interferingserum components without removing lipoproteins. All lipoproteins, exceptchylomicrons, are less than 100 nm in diameter. Prefiltration may alsobe provided to remove larger particles to enhance the lifespan of a finefilter (such as the 100 nm fine filter described above); for example, a2 μm pore-size filter will effectively remove larger particles.

The apparatus may comprise a reservoir of a cleaning fluid, such thatthe components of the apparatus may be flushed between samples. Thecleaning fluid may be as simple as saline solution, de-ionized water,saline made from filtered de-ionized water, or any of these with theaddition of detergents and surfactants. A specific embodiment of thecleaning fluid is a 40% v/v solution of Cleanz™ in water. The reservoirmay be connected to a cleaning conduit that joins the main conduitbetween the valve and counter (downstream from the sensor and the samplevessel). The reservoir may be positioned above the components to beflushed to impart sufficient hydraulic head to cause the cleaning fluidto flow through the components under the force of gravity. A pump may bepositioned to impart additional hydraulic head pressure to the cleaningfluid. While the valve is open the fluid will flush the end of theconduit positioned to collect the sample. While the valve is closed thefluid will flow through the conduit to the counter.

In one embodiment, the apparatus may be in communication with a controlunit. The control unit is in communication with the various componentsof the apparatus and may receive input from such components and/orcontrol the operation of such components. For example, the control unitmay comprise the data logger, which as described above, receives themeasurements of light scattering obtained from the light scatteringcounter. The control unit may contain executable programs to carry outfunctions associated with the methods described herein. For example, thecontrol unit may comprise an executable file used to deconvolute thedata generated. Furthermore, the control unit may comprise an executablefile that generates a particle number from the light scattering datameasured. In one aspect, the executable file is or contains an algorithmdescribed herein. In one embodiment, the control unit is a generalpurpose computer. The general purpose computer may be programmed tocarry out the functions described.

In another general embodiment, the apparatus comprises means forcontaining a liquid sample having vertically stratified fractions; meansfor conveying the lowest stratified fraction from the containing means;and means for counting particles configured to receive the loweststratified fraction from the containing means by way of the conveyingmeans. In some embodiments of the apparatus the means for counterparticles are means for measuring light scattering. The apparatus maycomprise means for flushing configured to flush the means for conveyingand to flush the means for counting particles. The apparatus may alsocomprise means for sensing air within the conveying means.

Turning now to FIG. 10, an embodiment of the apparatus is presentedcomprising a sampling needle configured to puncture the bottom of asample vessel; a tube having a first end and a second end, the first endconnected to the sampling needle to receive a liquid sample from theneedle; a light scattering counter connected to the second end of thetube and configured to measure light scattering in the sample whenconveyed through the tube; an optical sensor positioned to measure theoptical absorbance in the tube and capable of distinguishing air fromliquid; a primary pump configured to pump the sample from the needlethrough the tube to the counter; a solenoid valve downstream of thesensor and connected to the sensor to receive an electrical signalcausing the valve to close when air is detected by the sensor; and aflush reservoir connected to the tube.

I. Method of Calibration

Measurements of lipoprotein particle count may be calibrated bycomparing the results of other methods of counting or determining theconcentration of lipoprotein particles to photometric data. Apo B isparticularly useful in this regard for the atherogenic lipoproteins(Lp(a), LDL, IDL, or VLDL), as there is only one molecule of apoBpresent in a given particle of each atherogenic lipoprotein. Apo AI isparticularly useful in this regard for the HDL, as there are only 2-5molecules of Apo AI present in a given particle of HDL; the exact numberof Apo AI molecules may be determined for each HDL particle, or anaverage number of Apo AI molecules per HDL particle may be used in thecalculations described.

A method for calibrating the measurement of a particle count of anlipoprotein is provided, the method comprising: (i) obtaining aphotometric measurement of a lipoprotein from a calibration sample; (ii)measuring the molar concentration of specific marker, such as apoB forthe atherogenic lipoproteins or Apo AI for HDL, in the lipoproteinfraction of the calibration sample; and (iii) calculating a regressionbetween the photometric measurement and the molar concentration of themarker. The atherogenic lipoprotein may be selected from the groupconsisting of: Lp(a), IDL, LDL, and VLDL. The photometric measurementmay be any disclosed above as suitable for determining the particlecount of lipoproteins, including the measurement of light scattering.The regression may be an approximately linear regression, as would beexpected between a measurement of light scattering and the particlecount of a lipoprotein.

The molar concentration of apoB, apoA1 or other markers may be measuredby various means known in the art. For example, commercially availableimmunoassays can be used to quickly and accurately measure theconcentration of such markers in fractions containing lipoproteins froma sample. Such immunoassays may take any form in the art, includingfluorescent, enzymatic and magnetic assays. One suitable assay is theArchitect® system, available from Abbott Labs.

In many cases more than one calibration measurement will be necessary.Thus, the method may comprise obtaining a photometric measurement of theatherogenic lipoprotein from a second calibration sample; measuring themolar concentration of apoB in the second calibration sample; andcalculating a regression based on the photometric measurement in thecalibration sample, the molar concentration of apoB in the calibrationsample, the photometric measurement in the second calibration sample,and the molar concentration of apoB in the second calibration sample.Additional measurements may be made as discussed above, as necessary toestablish a sound regression.

J. Methods

The present disclosure also provides for a method of determining therisk of atherogenic disease in a subject, the method comprisingquantifying at least one serum lipoprotein in a sample from the subjectaccording to the methods disclosed herein and comparing the results withknown correlations between the at least one serum lipoproteinconcentration and the risk of atherogenic disease.

The method may further comprise obtaining a sample from the subject.Furthermore, the method may further comprise introducing the sample intoan apparatus disclosed herein.

In one embodiment the serum lipoprotein is LDL. In another embodiment,the serum lipoprotein is HDL. In still another embodiment, the serumlipoprotein is Lp(a). In still another embodiment, the serum lipoproteinis IDL. In still another embodiment, the serum lipoprotein is VLDL. Instill another embodiment, the serum lipoprotein is LDL and HDL. In stillanother embodiment, the serum lipoprotein is LDL and IDL. In stillanother embodiment, the serum lipoprotein is LDL, IDL and VLDL. In stillanother embodiment, the serum lipoprotein is LDL, IDL VLDL, HDL, andLp(a).

K. Examples

Sample Collection and Separation

A blood sample is collected from the subject. Such a sample is collectedas is known in the art, such as in a serum separator tube (SST) or plainred top serum tube. Serum is separated according to standard procedureand filtered to remove any clots, fibrin and any large interferingparticles.

In one embodiment, samples are subject to density gradientcentrifugation to separate lipid components. Density gradients wereprepared using either manual pipette and dispensing devices or anautomated liquid handler (such as the Tecan Genesis™) Multiple serumsamples may be processed at one time. In one embodiment, a batchconsisting of 16 serum samples is simultaneously prepared using anautomated liquid handler. The following steps were used in the followingexamples:

-   -   1. Pipette 50 μL serum and mix with 1950 μL of 1.21 g/mL KBr        solution.    -   2. Pipette 3.56 mL of 1.004 g/mL saline solution into a 5 mL        Beckman centrifuge tube.    -   3. Slowly underlay 1.4256 ml of above prepared serum:KBr mixture        to prepare a two density layer gradient.        Once the density gradient was prepared, all 16 centrifuge tubes        with density gradients were placed in a Beckman Vertical Rotor        (VTi 65) and centrifuged at 65,000 rpm for 47 minutes (including        acceleration and deceleration) using a Beckman Coulter Optima XL        100 ultracentrifuge.        Apparatus

Particle concentration (in terms of moles of particles per unit volume)of separated lipoprotein classes and subclasses in the centrifugate weremeasured by using a working embodiment of the apparatus (referred to inthis example simply as “the apparatus”). The apparatus is be anautomated continuous flow through analysis system consisting of anautomated specimen rack moving system, a tube piercing needle that canbe automatically raised to pierce the tube, an end of sample draindetector, a sample valve that closes and opens automatically asprogrammed to facilitate the flow of sample from centrifuge tube, apiston pump to drain the sample from the centrifuge tube at apredetermined flow rate, a programmed pneumatic valve that allows theflow of baseline solution when sample is not flowing, a narrow bore (0.8mm internal diameter) Teflon® tubing of a predetermined length (25inches) that connects the pump to the multi-angle laser light scatteringflow through detector (Wyatt Technology, Santa Barbara, Calif.) whichoutputs a light scattering signal proportional to the concentration oflipoprotein particles flowing through, an in line filter containing a100 nm pore-size filter to remove interfering blood components placedbetween pump and detector, and software (ASTRA) that continuouslycollects the digital signal from the detector as sample flows throughthe detector. The sample is run at a flow rate of 3 mL per minute, using25 inches of 0.8 mm Teflon™ tubing (resulting in a drain time of 1minute 45 seconds). As the separated lipoprotein particles flow throughthe flow cell of the detector a laser impinges on the particles. As aresult, they scatter light at various angles. The Wyatt instrument (DAWNHELEOS II) has 18 detectors (photodiodes) placed around the flow cellwhich collect signal from scattered light at their respective angles.The intensity of light is proportional to the type and number oflipoprotein particles flowing through. The signal is measured coming outof the detector placed at 90°. The method does not require any reagent,as it depends upon the physical phenomenon of light scattering. Suchembodiments of the method simplify the instrumentation as well as reducethe cost of analysis.

Analysis and Exemplary Results

As the separated lipoprotein particles (all lipoprotein particles areseparated based upon their density during ultracentrifugation with highdensity lipoprotein separating at the bottom of the centrifuge tube lowdensity lipoprotein in the middle and very low density lipoprotein atthe top) pass through the detector continuously during the draining ofcontents of centrifuge tube a continuous signal is obtained whichconsists of light scattering intensity peaks that correspond torespective lipoprotein classes as shown in FIGS. 11-14. The area of eachpeak is proportional to the respective number of particles of thatlipoprotein per unit volume. Since the single vertical spin densitygradient ultracentrifugation does not provide fully resolved (base lineseparated) peaks, deconvolution of the main continuous signal outputcurve into its component peaks corresponding to different lipoproteinpeaks as more fully explained above.

FIGS. 11-14 show the results of sample analysis using embodiments of themethod and apparatus. FIG. 11 shows a normal lipid profile, showingthree well-resolved peaks for the HDL, LDL, and VLDL fractions. FIG. 12shows a high-LDL lipid profile, also showing three well-resolved peaks.FIG. 13 shows a high-Lp(a) lipid profile, in which the Lp(a) peak fallsbetween the HDL peak and LDL peak; as can be seen the Lp(a) peak isquite visible. FIG. 14 shows a high-IDL lipid profile, in which apronounced IDL peak falls between the LDL peak and VLDL peak. Thedeconvoluted profiles corresponding to FIGS. 11-14 are shown in FIGS.15-18, respectively. The resulting deconvoluted profiles have threemajor peaks for fractions of decreasing density going from left to right(as the time variable increases) corresponding to the HDL, LDL, andVLDL; and two minor peaks corresponding to Lp(a) and IDL as describedabove.

Blank Spin

In order to assess interference due to solvents (KBr, saline, water,Cleanz™ and undissolved particles, a “blank” containing no serum (serumsubstituted with saline solution) was centrifuged and subjected to thelipoprotein counting protocol as described above. The blank profilessuggested a small drop in signal by KBr used for gradient preparationwhich was proportional to KBr concentration. Thus measurements from ablank run from the test sample were subtracted from the light scatteringmeasurements for the lipoprotein fractions to correct. This process isembedded in the deconvolution algorithm.

Controls

To monitor the stability of the signal from day to day three pooledserum samples with increasing LDL-R particle counts (obtained fromSolomon Park Research Laboratories, Seattle, Wash.) were run daily.

Precision

The precision and reproducibility of the lipoprotein particle countmethods disclosed was also examined for each lipoprotein class.

For LDL, IDL and VLDL precision/reproducibility studies, 4 pools ofsamples were prepared. Pool 1 had a triglyceride concentration of 70mg/dL and an LDL particle count of <1000 nmol/L. Pool 2 had atriglyceride concentration of 70 mg/dL and an LDL particle countof >1000 nmol/L. Pool 3 had a triglyceride concentration of 218 mg/dLand an LDL particle count of >1900 nmol/L. Pool 4 had a triglycerideconcentration of 320 mg/dL and an LDL particle count of >2100 nmol/L.For pools 1 and 2, 4 runs were made each day for 5 days, with each runcontaining 8 samples from each of pool 1 and 2 for a total of 160samples. For pools 3 and 4, 3 runs were made each day for 5 days, witheach run containing 8 samples from each of pool 3 and 4 for a total of120 samples. For these studies samples were prepared and analyzed by themethods and apparatus described herein using the separation conditionreferenced as Condition 2 herein. Average LDL particle concentrationsfor pool 1 were 886 nmol/L, for pool 2 were 1386 nmol/L, for pool 3 were1683 nmol/L and for pool 4 were 2125 nmol/L. Average IDL particleconcentrations for pool 1 were 43 nmol/1, for pool 2 were 66 nmol/L, forpool 3 were 149 nmol/L and for pool 4 were 210 nmol/1. Average VLDLparticle concentrations for pool 1 were 20 nmol/L, for pool 2 were 18nmol/L, for pool 3 were 115 nmol/L and for pool 4 were 252 nmol/L. Theresults are expressed in coefficient of variation (% CV) within each dayand between all days. The results for LDL, IDL and VLDL are shown belowand show good reproducibility.

LDL-Particle Reproducibility (% CV) Pool 2 Pool 4 DAY Pool 1 (% CV) (%CV) Pool 3 (% CV) (% CV) Day 1 2.4 2.8 5.1 7.4 Day 2 3.6 2.8 5.9 6.3 Day3 2.1 3.1 5.5 5.7 Day 4 2.4 2.9 6.7 6.6 Day 5 2.8 2.8 5.9 6.7 BetweenDays 3.1 3.3 6.3 6.6 (i.e All Results)

IDL-Particle Reproducibility (% CV) Pool 2 Pool 4 DAY Pool 1 (% CV) (%CV) Pool 3 (% CV) (% CV) Day 1 5.0 3.6 11.3 5.4 Day 2 7.2 6.0 16.3 8.2Day 3 4.2 4.3 9.4 8.1 Day 4 8.6 5.4 13.0 7.8 Day 5 5.1 4.8 11.4 7.4Between Days 7.8 5.8 13.0 7.9 (i.e All Results)

VLDL-Particle Reproducibility (% CV) Pool 2 Pool 4 DAY Pool 1 (% CV) (%CV) Pool 3 (% CV) (% CV) Day 1 4.4 2.9 5.3 3.2 Day 2 4.5 2.9 6.9 4.2 Day3 6.1 2.7 6.9 3.6 Day 4 4.0 2.5 7.1 3.6 Day 5 3.8 2.9 6.3 4.6 BetweenDays 4.7 2.9 6.7 4.2 (i.e All Results)

For HDL precision/reproducibility studies, 2 pools of samples wereprepared. Pool 1 had an apo AI concentration of 115 mg/dL (as measuredby the Architect/Abbot immunoassay system). Pool 2 had an apo AIconcentration of 255 mg/dL (as measured by the Architect/Abbotimmunoassay system). For pools 1 and 2, 3 runs were made each day for 6days, with each run containing 5 samples from each of pool 1 and 2 for atotal of 90 samples. For these studies samples were prepared andanalyzed by the methods and apparatus described herein using theseparation condition referenced as Condition 3 herein. The results areexpressed in coefficient of variation (% CV) within each day and betweenall days. The results for HDL are shown below and show goodreproducibility.

HDL-Particle Reproducibility (% CV) DAY Pool 1 (% CV) Pool 2 (% CV) Day1 20.0 7.0 Day 2 21.9 9.4 Day 3 29.7 14.1 Day 4 21.6 12.7 Day 5 18.5 8.4Day 6 16.5 11.0 Between Days 24.0 11.9 (i.e All Results)

For Lp(a) precision/reproducibility studies, 3 pools of samples wereprepared. Pool 1 had an Lp(a) concentration of 27 nmol/L. Pool 2 had anLp(a) concentration of 188 nmol/L. Pool 3 had an Lp(a) concentration of300 nmol/L. For pools 1 to 3, 3 runs were made each day for 6 days, witheach run containing 5 samples from each of pool 1 to 3 for a total of 90samples. For these studies samples were prepare and analyzed by themethods and apparatus described herein using the separation conditionreferenced as Condition 4 herein. The results are expressed incoefficient of variation (% CV) within each day and between all days.The results for Lp(a) are shown below and show good reproducibility.

Lp(a)-Particle Reproducibility (% CV) DAY Pool 1 (% CV) Pool 2 (% CV)Pool 3 (% CV) Day 1 16.3 8.4 5.1 Day 2 20.2 13.4 7.1 Day 3 23.1 14.1 5.8Day 4 22.0 11.9 5.4 Day 5 21.6 14.5 6.3 Day 6 16.9 12.0 9.9 Between Days25.4 14.2 7.7 (i.e. All Results)Linearity

Linearity of lipoprotein particle measurements were determined for eachof HDL, Lp(a), LDL, IDL and VLDL. For LDL, IDL and VLDL, thecentrifugation condition used was Condition 2. For HDL, thecentrifugation condition used was Condition 3. For Lp(a), thecentrifugation condition used was Condition 4. The method was carriedout as described herein using the apparatus described herein.

Generally, serial dilutions of a samples were made in the bottom layerof the density gradient solution (for LDL, IDL and VLDL, the bottomlayer was a 1.21. g/ml KBr solution). Multiple dilutions were maderanging from 0.4% to 30%. Lipoprotein particle concentrationmeasurements were performed in duplicate using the separation conditionsfor best resolution of each lipoprotein species and with the methods andapparatus disclosed herein. The resulting particle count for eachlipoprotein was plotted with its corresponding serum dilution using alinear regression analysis method. Plots for HDL, Lp(a), LDL, IDL andVLDL are shown in FIGS. 19-23, respectively. The R² value for the plotswere 0.996, 0.9890.998, 0.985 and 0.994, respectively for HDL, Lp(a),LDL, IDL and VLDL. This shows that lipoprotein particle measurement islinear up to the tested ranges.

Accuracy

The accuracy of the methods for determining lipoprotein particleconcentration (number) was also evaluated. For LDL, two comparisons weremade. First, comparison of average LDL particle concentration (number)was compared to serum apo B concentration. Second, comparison of averageLDL particle concentration (number) was compared to LDL particleconcentration (number) as measured by NMR.

It is known that each atherogenic lipid particle, including LDL,contains one apo B molecule and therefore one can visualize directcomparison of LDL particle number to apo B concentration in an LDLfraction. A good correlation can be anticipated between LDL particlenumber and whole serum apo B, at least in normotriglyceridemic subjects(triglyceride <150 mg/dL), since >90% of apo B is known to be present inLDL particles. This correlation may be reduced as triglyceridesconcentration increases since each triglyceride-rich lipoprotein (IDLand VLDL) also contain one molecule of apo B.

Therefore, LDL particle number as determined by the methods describedherein (using Condition 2 as the centrifugation condition) was comparedwith serum apo B concentration in serum samples (SST) collected from 40apparently healthy individuals (similar results were obtained whenCondition 1 was used; data not shown). The turbidimetry immunoassay byAbbott/Architect C8000 was used for serum apo B measurement. FIG. 24shows a plot of the comparison of average LDL particle number obtainedand apo B obtained from Abbott/Architect C8000. The above results show agood correlation between LDL average particle number and serum apo Bconcentration.

In addition, average LDL particle number was compared to an NMRtechnique. The comparison was made with the same 239 samples describedabove. The results of this comparison (average LDL number obtained from3 separate instruments and NMR results) are shown in FIG. 25. The aboveresults show a reasonable agreement between the two methods. It shouldbe noted that LDL particle count measured by the methods describedherein does not include Lp(a) and IDL, which are generally consideredcomponents of LDL. It is not clear whether LDL particle numbers from NMRmethod includes Lp(a) and or IDL. Thus, a high correlation and agreementbetween the two methods may not be expected. Moreover, the two methodsare based on entirely two different principles.

For IDL and VLDL fractions, comparison between the average lipoproteinparticle counts was made using the concentration of cholesterol measurein the IDL and VLDL fractions as determined by the VAP Assay(Atherotech, Inc., Birmingham, Ala.; methods described in U.S. Pat. Nos.5,284,773 and 5,633,168, which are hereby incorporated by reference forsuch teaching). IDL and VLDL particle number as determined by themethods described herein (using Condition 2 as the centrifugationcondition) was compared with cholesterol content as determined by theVAP assay.

The results are shown in FIGS. 26 and 27 for IDL and VLDL, respectively.As can be seen in FIG. 26, the comparison of IDL particle concentration(number) versus IDL cholesterol produced a linear plot with a slope of3.72 and an R of 0.882. As can be seen in FIG. 27, the comparison ofVLDL particle concentration (number) versus VLDL cholesterol produced alinear plot with a slope of 2.9 and an R of 0.862. Both results show agood correlation between IDL/VLDL particle number and cholesterol.

For HDL, HDL particle number as determined by the methods describedherein (using Condition 3 as the centrifugation condition) was comparedwith serum apo AI concentration in serum samples (SST) collected from 88individuals. The turbidimetry immunoassay by Abbott/Architect C8000 wasused for serum apo AI measurement. FIG. 28 shows a plot of thecomparison of average HDL particle number and apo AI obtained fromAbbott/Architect C8000. The above results show a good correlationbetween HDL average particle number and serum apo AI concentration.While the R value reported for HDL (0.63) was not as high as thatreported for LDL, the lower correlation observed is likely a function ofthe heterogeneous nature of apo AI distribution on HDL particles ascompared to the homogenous distribution of apo B on LDL articles.

For Lp(a), Lp(a) particle number as determined by the methods describedherein (using Condition 4 as the centrifugation condition) was comparedwith Lp(a) concentration in serum samples (SST) collected from 78individuals. The Lp(a) immunoassay by Randox Laboratories was used tomeasure Lp(a). FIG. 29 shows a plot of the comparison of average Lp(a)particle number as determined by the methods described herein and Lp(a)results obtained from the Randox immunoassay. The above results show agood correlation between Lp(a) average particle number and serum Lp(a)concentration.

Deconvolution

In one embodiment, the deconvolution algorithm used herein is based onplurality of basis of curves that can be manipulated to provide a bestfit to any given lipoprotein profile. In one embodiment, there aremultiply basis curves for a given lipoprotein class. In an alternateembodiment, there is a single curve for a given lipoprotein class. Thenumber and location of the subcurves is based, in one embodiment, onempirical observation and testing with lipoprotein samples to determinea baseline for the analysis. In a particular embodiment, 14 basis curvesare used. In a particular embodiment, 14 basis curves are used, with 5curves used for the HDL class, 1 curve for the Lp(a) class, 3 curves forthe LDL class, 2 curves for the IDL class and 3 curves for the VLDLclass.

The fit is based on non-linear equations and involves one or moreiterations to converge to a solution. The curves are based on a fourparameter Weibull curve that has been used to describe particle sizedistribution. The Weibull equation is a well known equation commonlyused in statistical and reliability calculations. The use of the Weibullequation has the following advantages. First, it requires only fourparameters. Second, the equation assumes a wide continuum of curveshapes and sizes. Third, the area under any unit amplitude curve isalways=1.00. Fourth, the equation is analytically differentiable on allfour parameters (i.e., the curves are smooth)

Using the Weibull equation, the curves are all defined at any point X bya single

$\frac{\beta}{\alpha^{\beta}} \cdot \left( {X - \mu} \right)^{\beta - 1} \cdot e^{- {(\frac{X - \mu}{\alpha})}^{\beta}}$equation (Equation 4), where: a controls the curve width; β control thecurve shape; and μ controls the curve location.

By simply varying the parameter values, a wide variety of curve shapesand sizes is possible. Four example curves generated using the variablesbelow are shown in FIG. 30

1 A := 1.0 α := 15 β := 1.25 μ := 10 Curve1_(i) := Weibull (A, α, β, μ,X_(i)) 2 A := 1.0 α := 25 β := 2 μ := 40 Curve2_(i) := Weibull (A, α, β,μ, X_(i)) 3 A := 1.0 α := 35 β := 3.5 μ := 80 Curve3_(i) := Weibull (A,α, β, μ, X_(i)) 4 A := 1.0 α := 45 β := 5 μ := 120 Curve4_(i) := Weibull(A, α, β, μ, X_(i))

To account for minor process changes and variation in pump speeds,viscosity, and temperature and other factors, the time scale of theprofiles is normalized to a common scale. In one embodiment, the scaleis arbitrarily set to 0-200. Each profile is segmented based on signalsfrom the data set that uses the expected timing from separationprocedure (such as ultracentrifugation) and morphological features foundin the profile shapes.

Because the curves are non-linear, a simple linear regression is notsufficient to deconvolute the curves. In one embodiment, the LevenbergMarquadt is used to deconvolute the curves. This algorithm uses a searchand step method to find a good fit for each curve. In one embodiment,all four parameters can be constrained to fit within a specified range.In particular, the range of motion along the X-Axis for each curve isconstrained so that the curves occupy a defined position based on theclass of lipoprotein represented by the curve. In addition, theamplitude parameters are required to be positive.

An example fit is shown below. It shows all 14 of the minor subcurves.Note the varying shapes and amplitudes (FIG. 31). In FIG. 31 (as well asFIG. 32 below), the dark line is the particle concentration profilecollected with a light scattering detector, which is deconvoluted intothe various subcurves below. After the minor subcurves are generated,they are grouped and summed into higher level curves. In this case,curves for the HDL, LPa, LDL, IDL, and VLDL lipoprotein classes (FIG.32). The area under each higher level curve is then determined asdescribed herein.

L. Conclusions

The foregoing description illustrates and describes the processes,machines, manufactures, compositions of matter, and other teachings ofthe present disclosure. Additionally, the disclosure shows and describesonly certain embodiments of the processes, machines, manufactures,compositions of matter, and other teachings disclosed, but, as mentionedabove, it is to be understood that the teachings of the presentdisclosure are capable of use in various other combinations,modifications, and environments and is capable of changes ormodifications within the scope of the teachings as expressed herein,commensurate with the skill and/or knowledge of a person having ordinaryskill in the relevant art. The embodiments described hereinabove arefurther intended to explain certain best modes known of practicing theprocesses, machines, manufactures, compositions of matter, and otherteachings of the present disclosure and to enable others skilled in theart to utilize the teachings of the present disclosure in such, orother, embodiments and with the various modifications required by theparticular applications or uses. Accordingly, the processes, machines,manufactures, compositions of matter, and other teachings of the presentdisclosure are not intended to limit the exact embodiments and examplesdisclosed herein. It is to be understood that any given elements of thedisclosed embodiments may be embodied in a single structure, a singlestep, a single substance, or the like. Similarly, a given element of thedisclosed embodiment may be embodied in multiple structures, steps,substances, or the like. Any section headings herein are provided onlyfor consistency with the suggestions of 37 C.F.R. § 1.77 or otherwise toprovide organizational queues. These headings shall not limit orcharacterize the disclosure set forth herein.

What is claimed:
 1. A method of measuring lipoprotein particle number ina sample comprising both Lp(a) and LDL lipoprotein, the methodcomprising: a. separating the Lp(a) lipoprotein into a Lp(a) fractionand the LDL lipoprotein into an LDL fraction by centrifugation; b.sequentially introducing the Lp(a) fraction and the LDL fraction into adetector; c. obtaining a photometric measurement in the Lp(a) fractionand the LDL fraction; and d. calculating a Lp(a) particle number for theLp(a) fraction that is a function of the photometric measurement in theLp(a) fraction and calculating a LDL particle count for the LDL fractionthat is a function of the photometric measurement in the LDL fraction.2. The method claim 1, wherein the function is an approximately linearfunction.
 3. The method of claim 1, wherein separation is accomplishedusing density-gradient centrifugation.
 4. The method of claim 1, whereinthe sample is contained in a sample vessel and step (b) is accomplishedby sampling the sample vessel from the bottom so as to introduce collectthe fractions in descending order of density.
 5. The method of claim 1,wherein the sample is selected from the group consisting of: a bloodsample and a blood serum sample.
 6. The method of claim 1 furthercomprising the steps of: a. separating at least one additional lipidfraction in the sample by centrifugation, the at least one additionallipid fraction selected from the group consisting of: a VLDL fraction,an IDL fraction and an HDL fraction; b. obtaining a photometricmeasurement in the at least one additional lipid fraction; and c.calculating a particle number for the at least one additional lipidfraction, wherein the particle count is a function of the photometricmeasurement in the at least one additional lipid fraction.
 7. The methodof claim 6, wherein the at least one additional lipid fraction is theHDL fraction.
 8. The method of claim 6, wherein the at least oneadditional lipid fraction is the VLDL fraction.
 9. The method of claim6, wherein the at least one additional lipid fraction is the IDLfraction.
 10. The method of claim 6, wherein the at least one additionallipid fraction is the HDL fraction and one or more lipid fractionsselected from the group consisting of: the VLDL fraction, and the IDLfraction.
 11. The method of claim 6, wherein the at least one additionallipid fraction is the VLDL fraction and one or more lipid fractionsselected from the group consisting of: the HDL fraction, and the IDLfraction.
 12. The method of claim 6, wherein the at least one additionallipid fraction is the IDL fraction and one or more lipid fractionsselected from the group consisting of: the VLDL fraction, and the HDLfraction.
 13. The method of claim 6, wherein the at least one additionallipid fraction is the VLDL fraction, the HDL fraction and the IDLfraction.
 14. The method of claim 1, wherein the sample is not subjectto any additional purification steps to isolate or remove the Lp(a) orthe LDL lipoprotein.